Man–Machine–Environment System Engineering : Proceedings of the 19th International Conference on MMESE [1st ed. 2020] 978-981-13-8778-4, 978-981-13-8779-1

Table of contents :
Front Matter ....Pages i-xxii
Front Matter ....Pages 1-1
Research on the Characteristics of Physical Fitness Testing for Special Operation Forces of Military Powers and Their Reference Value (Chunlai Wang)....Pages 3-10
Comparative Study of Acupuncture–Moxibustion and Transcranial Micro-Current Stimulation in Therapy of Altitude Hypoxia Headache and Insomnia (Yongsheng Chen, Dalong Guo)....Pages 11-20
Scientific Data Sharing Platform Using Behavior Study Based on Extended TAM Model (Jianping Liu, Jian Wang, Guomin Zhou, Guilan Zhang, Yao Pan, Xu Sa et al.)....Pages 21-30
Subjectively and Objectively Measured Hazard Perception Ability of Young Chinese Drivers (Lingsen Hua, Long Sun, Yidan Ma)....Pages 31-36
Experimental Research on Layout Accessibility of Individual Load-Carrying Equipment (Yaping Wang, Shanlin ChenCai)....Pages 37-45
Evaluation and Strategy Analysis of Students’ Mental Health in Semi-military Schools (Min Wang, Jintao Yu, Peng Wang)....Pages 47-54
Study on Classification and Characteristic of Type of Lower Part of Body of Female College Students (Jiandie Lin, Yuxiu Yan, Zimin Jin, Lu Lin)....Pages 55-63
Correlation Study of Football Shin Guards Oppression and Muscle Fatigue During Sports (Yifei Mu, Zimin Jin, Jing Jin, Yuhan He, Yuxiu Yan)....Pages 65-73
Influence of Wristband Tightness on the Protection of Wrist Joint in Table Tennis (Mengyun Zhou, Zimin Jin, Jing Jin, Wenli Li, Yuxiu Yan)....Pages 75-83
Optimal Design of the Elastic Unit for the Serial Elastic Hip Joint of the Lower Extremity Exoskeleton (Bingshan Hu, Guanming Cheng, Hongrun Lu, Hongliu Yu)....Pages 85-94
Analysis About the Influence of Protective Equipment on the Upper Limbs’ Range of Motion (Chenming Li, Tianhao Wang, Yuhong Shen)....Pages 95-101
Biomechanical Study of Long-Segment Spine Instrumentation: The Effect of Cross-Links (Tianhao Wang, Chenming Li, Yan Wang)....Pages 103-111
Microexpression Recognition Training in Left-Behind Children in China (Xueling Zhang, Lei Chen, Gaojie Fan, Huajie Sui, Xunbing Shen)....Pages 113-120
Research on the Relationship Between Personality and Speed Skills Training of Military Academy Cadets (Nan Men, Qi Gong, Cheng Jin, Haitao Zhao, Pengdong Zhang, Zhibing Pang)....Pages 121-131
Research on Connection Between Physiological Index and Endurance Training on Military Academy Cadets (Pengdong Zhang, Zhenyou Zhang, Xuechen Yao, Zhibing Pang)....Pages 133-138
Research on the Generation Law of Single-Machine Operation Skills (Haitao Zhao, Cheng Jin, Xing Su, Genhua Qi, Zhibing Pang)....Pages 139-146
Eye Gaze Orientation and Pupil Size Variation on Time-Series Vigilance Task (Deqian Zhang, Wenjiao Cheng, Hezhi Yang)....Pages 147-152
Research on Psychological Management of Officers and Men in MOOTW (Zaochen Liu, Peng Gong, Yunqiang Xiang, Doudou Shan, Ailing Cheng)....Pages 153-158
The Influences of Capability and Character on Human’s Manual Dexterity (Shun Yao, Shengping Zhao, Zhongting Zhou)....Pages 159-168
Sniper Selection Index Measurement and Factor Weight Analysis (Weiming Deng, Yubo Deng, Liwei Gong, Lu Hua, Shikun Wang, Fei Ji)....Pages 169-175
Investigation on the Index of Sniper Selection and Gray Correlation Analysis (Zhiwei Zhu, Weiming Deng, Bing Zhang, Shandong Mao, Chan Zhang)....Pages 177-185
Researches on the Eye-Movement Mode of Chinese College Students in Reading English Websites (Lijun Jiang, Bingbing Huang, Zhelin Li, Zhanghong Wu, Lu Lv)....Pages 187-195
Research on the Needs of Elderly Users of Electronic Sphygmomanometer Design (Nan Li, Liqing Huang)....Pages 197-204
Analysis of Syncope Problem in Single Elderly and Application of Related Monitoring Products (Chen Ni)....Pages 205-215
Physiological Measures of Mental Workload: Evidence from Empirical Studies (Da Tao, Xu Zhang, Jian Cai, Haibo Tan, Xiaoyan Zhang, Tingru Zhang)....Pages 217-225
Ideological Method of Constructing Geometric Model of Human Heat Transfer Process (Sina Dang, Hongjun Xue, Xiaoyan Zhang, Jue Qu, Chengwen Zhong, Siyu Chen)....Pages 227-233
Study of Correlation Between Subjective Symptoms and Ergonomic Load Index of Automobile Assembly Workers (Deshan Yin, Xiaofei Zhang, Yi Zhao, Shulin Zhou)....Pages 235-244
Front Matter ....Pages 245-245
Lane Detection Algorithm Based on Inverse Perspective Mapping (Dong Chen, Zonghao Tian, Xiaolong Zhang)....Pages 247-255
A Preliminary Study on the Attractive Factors of Car Headlight Form Design (Huan Lin, Shijian Luo, Chen Zhu, Hongzhuan Ding, Huiming Yi, Ze Bian et al.)....Pages 257-264
Design and Optimization of Command Software Interface (Chunfeng Zhu, Danhua Sun, Zuohui Bao, XiaoFei Zhai)....Pages 265-271
A Subjective Assessment Method of Aerospace Image Quality Based on Human Visual System (Wuyuan Zhou, Haoting Liu, Chang Guo, Weidong Dong, Shuo Yang, Shunliang Pan et al.)....Pages 273-280
The Cabin Layout Project of the Ergonomic Evaluation Methods Study (Sijuan Zheng, Li Li, Wenjun Guo, Fang Xie, Liang Ling, Zhongliang Wei)....Pages 281-287
Development of an Aviation Emergency Coping Ability Evaluation Instrument (Qingfeng Liu, Yang Lv, Xiaochao Guo, Fei Peng, Yu Bai, Jian Du et al.)....Pages 289-297
Developing Direction of Air Defense Electron-Magnetic Gun Based on Demand of Countering Air and Missile Threat (Jinxin Li, Yong Zhang, Guiqi Liu, Ruifeng Zhao, Tao Li, C. Mei)....Pages 299-306
The Integration Design Parameters Selection Method of Equipment Performance and Testing (Guanqian Deng, Suqiong Kuang, Yingjie Lv, Guiyou Hao, Shaojun Qi, Yuewen An)....Pages 307-314
The Integration Design Process and Method of Equipment Performance and Testing (Guanqian Deng, Suqiong Kuang, Yingjie Lv, Guiyou Hao, Shaojun Qi, Pengjun Wang)....Pages 315-319
Design and Control of a Novel Pneumatic Soft Upper Limb Exoskeleton for Rehabilitation (Qiaoling Meng, Zhongzhe Chen, Yingchen Li, Zhenji Tian, Zhiyu Wu, Lei Li et al.)....Pages 321-328
Sketch Recognition and Interaction Design Based on Machine Learning (Wei Feng, WanFeng Mao, Baiqiao Huang, Guanqun Zhang, Pengyi Zhang, Xing Li et al.)....Pages 329-337
Development and Application of Test Software of Fine Operation Ability of Directional Motion (Weicai Tang, Yi Xiao, Fenggang Xu, Chunhui Wang)....Pages 339-346
Research on Key Technology to Underwater Robotic Arm (Shang Huan, Suqin Wang, Xu Han, Jianzhi Bi)....Pages 347-356
A Portable Variable Stiffness Unpowered Aided Exoskeleton Design (Luoqin Yu, Kai Wang, Tianning Chen)....Pages 357-367
Expressway Vehicle Management System Based on Vehicle Face Recognition (Chan Zhang, Lijian Deng, Qicai Du, Weiming Deng)....Pages 369-376
The Research of Multilevel Takeover Alert Information Design for Highly Automated Driving Vehicles (Lijun Jiang, Simin Cao, Zhelin Li, Yu Zhang, Zequan Zhang)....Pages 377-384
Study on Application of Transfer Path on Micro-vibration Test for Satellite (Gongbo Ma, Yao Wu, Dong Wang, Zhiyong Yue, Jiang Yang, Rui Wang)....Pages 385-393
Hierarchical Processing Model Based on Multi-modality Interaction Design (Aiguo Lu, Bo Dong, Feiran Hu)....Pages 395-404
Application of Pipeline Ventilation Efficiency Test in Sanitary Ventilation Engineering (Huijun Zhang, Shulin Zhou)....Pages 405-415
The Influence on the Limit Flow Ratio Caused by the Change of the Area of the Exhaust Hood Face in the Design of Push–Pull Ventilation (Shulin Zhou, Bin Yang, Huijun Zhang)....Pages 417-423
Front Matter ....Pages 425-425
Simulation and Analysis of Sun Illumination on a Satellite (Na Zheng, Haoting Liu, Weidong Dong, Shuo Yang, Shunliang Pan)....Pages 427-434
Control Logic Design Based on Modeling of Aircraft Cockpit Temperature Control System (Yudi Liu, Chengyun Wu, Zhiyong Min, Xuhan Zhang)....Pages 435-443
Simulation Method of Jamming Performance of Projectile-Carried Communication Jammer Based on OPNET Platform (Lizhi Qian, Jie Zhang, Dong Chen)....Pages 445-451
Experimental Study of Intelligent Lighting Control Method for Dark Field Surveillance (Haoting Liu, Chang Guo, Shuo Yang, Weidong Dong, Shunliang Pan)....Pages 453-460
Investigating the Comfort Distance of Chinese in Eight Directions (Xiaoqing Yu, Yu-Chi Lee)....Pages 461-468
Design and Application of a Ventilation System in a Washing Board Room Based on Numerical Simulation (Bin Yang, Jianwu Chen, Shasha Liang, Shulin Zhou, Yanqiu Sun, Yunmeng Li)....Pages 469-475
Real-Time and Accurate Target Location Method Based on Artificial Mark (Qiaoling Meng, Haitao Wang, Hongliu Yu, Meng Wang, Bingshan Hu)....Pages 477-484
Modeling and Analysis of Fire Control Radar Capabilities Against Passive Jamming (Wei Yu, Meng Kang, Xiaonian Wang, Jiang Luo, Yan Sun)....Pages 485-491
Inverse Design for Thermal Environment and Energy Consumption of Vehicular Cabins with PSO–CFD Method (Zheming Tong, Hao Liu, Shuiguang Tong, Jiwang Xu)....Pages 493-501
Developing a Vehicle Thermal Management System with Fuzzy Control Method (Zheming Tong, Wenjun Shi, Shuiguang Tong, Yue Li)....Pages 503-512
Experimental Study on Color Requirements of Paratroopers for Transport Aircraft Cabin (Xiaochao Guo, Yanyan Wang, Jian Du, Yu Bai, Qingfeng Liu, Duanqin Xiong et al.)....Pages 513-520
Subjective Comprehensive Evaluation of LED Light Environment in Confined Space (Chuan Wang, Shenghang Xu, Guangjiang Wu, Jun Peng, Fenzhou Shi, Changbo Liao)....Pages 521-529
Quantitative Analysis of Relationship Between Subjective and Objective Evaluation Indexes of LED Light Environment in Confined Space (Jian Zhang, Shenghang Xu, Jun Peng, Guangjiang Wu, Yang Yuan, Chuan Wang)....Pages 531-539
Complexity Assessment of Battlefield Electromagnetic Environment (Hongjun Cheng, Hao Jiang, Xujiao Wang)....Pages 541-548
Decompression Analysis for Maximum Effective Flow Area in Emergency Descent (Huayuan Liu, Shiquan Lin)....Pages 549-555
Diversification in Developing Lunar Dust Simulant (Hao Sun, Yao Wu, Jiang Yang, Rui Wang, Haiyang Gao, Yanjing Yang)....Pages 557-565
Design and Application of Test Process Management System for Spacecraft Vacuum Thermal Test (Xinming Su, Dongliang Wu, Zelin Fei, Jing Wang, Chang Liu)....Pages 567-575
Theory and Simulation Analysis of Acoustic Characteristics of a High-Level Traveling-Wave Acoustic Environment Simulation Device (Yao Wu, Zhiqiang Shen, Qiang Jiang, Guiqian Fang, Xinming Li, Jungang Zhang et al.)....Pages 577-587
Front Matter ....Pages 589-589
Design of Central Console in Large Mining Excavator Based on Ergonomics (Hongrui Zhang, Jiajun Ren, Aifeng Li, Jing Zhao)....Pages 591-598
The Influence of a Certain Type of Radar Operator’s Operating Ability on the Operational Effectiveness of Equipment (Hongyan Ou, Di Wu, Lin Chen, Zhibing Pang, Zhiqinq Liu, Jifeng Wang et al.)....Pages 599-606
Verifying Experimental Study on Colorful Display Schemes for See-through Display Information (Duanqin Xiong, Wanli Lou, Qingfeng Liu, Yu Bai, Tao Jiang, Yanyan Wang et al.)....Pages 607-615
A Software Approach of Human–Machine Interface Ergonomics Evaluation (Hongjun Xue, Ye Yuan, Jiayu Chen, Xiaoyan Zhang)....Pages 617-622
Ergonomics Evaluation of Cabin Human–Machine Interface Based on SHEL Model (Hongjun Xue, Jiayu Chen, Ye Yuan, Xiaoyan Zhang)....Pages 623-629
Study on Human–Machine Interface Design of Nuclear Power Plant Control Room (Shenghang Xu, Yiqian Wu, Chuan Wang)....Pages 631-639
Intelligent Human–Computer Interaction Design Based on Multi-modality Technology Applied to Shipborne Command and Control System (Aiguo Lu, Wen Li, Chao Pan)....Pages 641-649
Front Matter ....Pages 651-651
Influence of Cut-in Situation on Driving Behavior of the Following Car Drivers (Fuwei Wu, Rui Fu, Xin Wang, Jinfeng Liu)....Pages 653-660
The Effect of Personal Protective Equipment on the Physiological Stress of Rescue Workers (Tianhao Wang, Chenming Li, Yan Wang)....Pages 661-669
Plateau Environment’s Effects on College Students Psychological Health Conditions (Yu Luo, Peijun Zheng, Zhenqin Wang, Yaqiong Chen, Xuechen Yao)....Pages 671-674
Research on Damage Mechanism of Projectile Fragments to Personnel Targets in Battlefield Environment (Yong Li)....Pages 675-683
Experimental Study on the Effect of Motion Sickness on 4D Movie Viewing Comfort (Jinjin Wang, Zhengqing Jiang)....Pages 685-693
The Effects of Continuous Conversation and Task Complexity on Usability of an AI-Based Conversational Agent in Smart Home Environments (Jingya Guo, Da Tao, Chen Yang)....Pages 695-703
Front Matter ....Pages 705-705
Electromagnetic Compatibility Design of a Certain Information System Command Vehicle in Complex Electromagnetic Environment (Qiang Liu, Xiaofei Zhai, Zuohui Bao, Yangke Liu, Yong Wang)....Pages 707-713
Construction of Criterion for Applicability of Multi-mode Seeker to Complex Meteorology and Development of the Application Software (Shidong Fang, Dong Chen, Quanli Ning, Liang Ma, Junjian Li)....Pages 715-722
Front Matter ....Pages 723-723
Practice and Research on the Modern Residential District Planning and Design (Zhen Li, Heng Chen, Fang Liu)....Pages 725-731
Ergonomics Analysis of Hand-Held Grinding Operation Working Posture Based on Jack (Yanqiu Sun, Jianwu Chen, Zhenlong Lu, Bin Yang, Weijiang Liu)....Pages 733-740
Establishment Methodology of Comfort Parameters Series for Civil Aircraft Cabin (Xuhan Zhang, Chengyun Wu, Guangwen Wang, Xiaojin Xiao)....Pages 741-749
Determination of Fighter Cockpit DEP Based on WEPs of Pilots in Simulated Flight (Xiaochao Guo, Yanyan Wang, Yu Bai, Duanqin Xiong, Jian Du, Qingfeng Liu)....Pages 751-757
Fuel Gas Enterprise Accident Risk Assessment Based on BP Neural Network (Qiquan Wang, Cheng Cheng, Chao Zhang, Jiahe Zhang, Kaiyuan Ning)....Pages 759-767
Digital Human Modeling for Performance Evaluation During Marine Vehicle Operation (Yuan Liu, Tuoyang Zhou, Ning Li, Hao Li, Tiancheng Huang)....Pages 769-777
The Maintenance Control Logic Design of Virtual Maintenance Training System of a Certain Type of Equipment Based on Operation Mechanism (Yong Wang, Fang Meng, Zuohui Bao, Hongtao Kan, Yangke Liu, Qiang Liu)....Pages 779-786
Research on the Management of Equipment Use Risk Based on “Man-Machine-Environment” Model (Cheng Jin, Genhua Qi, Yao Xiao, Haitao Zhao, Zuohui Bao, Yu Luo)....Pages 787-792
Validation of Ergonomics Evaluation Method Based on Eye Tracking Technology in Unmanned Aerial System (Yanyan Wang, Bo Gu, Xiaochao Guo, Duanqin Xiong, Yu Bai, Jian Du et al.)....Pages 793-801
Research on Essential Connotation of Military Management Revolution Centering on Effectiveness (Peng Gong, Dinghan Feng, Huiyong Wang, Ye Tao)....Pages 803-810
Research on the Safety Risk Management Model in Military Training (Zhenguo Mei, Chang Mei, Peng Gong, Weifei Wu, Ye Tao, Wenying Xing)....Pages 811-818
Practical Significance, Main Problems, and Countermeasures of Safety Risk Management in Military Railway Transportation (Weifei Wu, Zhenguo Mei, Chang Mei, Peng Gong, Ye Tao)....Pages 819-825
Study on the Upper Flange Width on Grinding Worktable and Its Ergonomics Evaluation (Jianwu Chen, Yanqiu Sun, Xiaolei Zhang, Zhenfang Chen, Bin Yang, Weijiang Liu)....Pages 827-835
A Linguistic 2-Tuple Multi-criteria Decision-Making Model for Military Training Assessment (Haiming Li, Gang Yu, Guobin Shang, Chongxin Tian)....Pages 837-846
The Mechanism of Servant Leadership on the Safety Performance of High-Speed Railway Drivers (Long Ye, Zheng Yang, Ming Guo)....Pages 847-854
Research on Human–Machine Motion-Sensing Factors of Large VR Amusement Equipment Based on AHP Algorithm (Wenxu Cong, Shaohua Wang, Zhengqing Jiang)....Pages 855-866
Study on Design of Vehicle Driver’s Control Area Based on Man-Machine System (Tong Wu, Yuqi Yuan)....Pages 867-873
Usability Study of Signage Way-Finding System in Large Public Space (Jinxing Yang, Xinle Bao, Ying Zhu, Duming Wang)....Pages 875-884
Application of Virtual Human Factor Verification to Fire Accidents at the Main Control Room in Nuclear Power Plant (Zhiyao Liu, Qichao Zhao, Linwu Sun, Yantong Luo)....Pages 885-892
Front Matter ....Pages 893-893
Base on Transportation and Separation of Municipal Solid Waste of Human-Machine-Environment System Research (Ziman Liu, Yuanchun Huang, Yifan Zhuang, Zhigang Liu, Xing Zhao)....Pages 895-901
Evaluation on the Man-Machine-Environment System of University Library (Kunzhu Zhang, Xinpo Wei, Quan Yuan, Jingyi Liu)....Pages 903-911
Human-Machine-Environment System Evaluation in Nuclear Power Plant Based on Virtual Reality Technology (Linwu Sun, Zhiyao Liu, Ming Jia, Qichao Zhao)....Pages 913-920

Citation preview

Lecture Notes in Electrical Engineering 576

Shengzhao Long Balbir S. Dhillon Editors

Man–Machine– Environment System Engineering Proceedings of the 19th International Conference on MMESE

Lecture Notes in Electrical Engineering Volume 576

Series Editors Leopoldo Angrisani, Department of Electrical and Information Technologies Engineering, University of Napoli Federico II, Naples, Italy Marco Arteaga, Departament de Control y Robótica, Universidad Nacional Autónoma de México, Coyoacán, Mexico Bijaya Ketan Panigrahi, Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, Delhi, India Samarjit Chakraborty, Fakultät für Elektrotechnik und Informationstechnik, TU München, Munich, Germany Jiming Chen, Zhejiang University, Hangzhou, Zhejiang, China Shanben Chen, Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China Tan Kay Chen, Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore Rüdiger Dillmann, Humanoids and Intelligent Systems Lab, Karlsruhe Institute for Technology, Karlsruhe, Baden-Württemberg, Germany Haibin Duan, Beijing University of Aeronautics and Astronautics, Beijing, China Gianluigi Ferrari, Università di Parma, Parma, Italy Manuel Ferre, Centre for Automation and Robotics CAR (UPM-CSIC), Universidad Politécnica de Madrid, Madrid, Spain Sandra Hirche, Department of Electrical Engineering and Information Science, Technische Universität München, Munich, Germany Faryar Jabbari, Department of Mechanical and Aerospace Engineering, University of California, Irvine, CA, USA Limin Jia, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Alaa Khamis, German University in Egypt El Tagamoa El Khames, New Cairo City, Egypt Torsten Kroeger, Stanford University, Stanford, CA, USA Qilian Liang, Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA Ferran Martin, Departament d’Enginyeria Electrònica, Universitat Autònoma de Barcelona, Bellaterra, Barcelona, Spain Tan Cher Ming, College of Engineering, Nanyang Technological University, Singapore, Singapore Wolfgang Minker, Institute of Information Technology, University of Ulm, Ulm, Germany Pradeep Misra, Department of Electrical Engineering, Wright State University, Dayton, OH, USA Sebastian Möller, Quality and Usability Lab, TU Berlin, Berlin, Germany Subhas Mukhopadhyay, School of Engineering & Advanced Technology, Massey University, Palmerston North, Manawatu-Wanganui, New Zealand Cun-Zheng Ning, Electrical Engineering, Arizona State University, Tempe, AZ, USA Toyoaki Nishida, Graduate School of Informatics, Kyoto University, Kyoto, Japan Federica Pascucci, Dipartimento di Ingegneria, Università degli Studi “Roma Tre”, Rome, Italy Yong Qin, State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China Gan Woon Seng, School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore Joachim Speidel, Institute of Telecommunications, Universität Stuttgart, Stuttgart, Baden-Württemberg, Germany Germano Veiga, Campus da FEUP, INESC Porto, Porto, Portugal Haitao Wu, Academy of Opto-electronics, Chinese Academy of Sciences, Beijing, China Junjie James Zhang, Charlotte, NC, USA

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Shengzhao Long Balbir S. Dhillon •

Editors

Man–Machine–Environment System Engineering Proceedings of the 19th International Conference on MMESE

123

Editors Shengzhao Long Astronaut Research and Training Center of China Beijing, China

Balbir S. Dhillon University of Ottawa Ottawa, ON, Canada

ISSN 1876-1100 ISSN 1876-1119 (electronic) Lecture Notes in Electrical Engineering ISBN 978-981-13-8778-4 ISBN 978-981-13-8779-1 (eBook) https://doi.org/10.1007/978-981-13-8779-1 © Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Grandness Scientist Xuesen Qian’s Sky-high Estimation for the Man–Machine–Environment System Engineering

Grandness Scientist Xuesen Qian’s Congratulatory Letter to the 20th Anniversary Commemorative Conference of Man–Machine–Environment System Engineering Foundation

Program and Technical Committee Information

General Chairman Professor Shengzhao Long, Astronaut Research and Training Center of China

Program Committee Chairman Professor Balbir S. Dhillon, University of Ottawa, Canada

Technical Committee Chairman Professor Enrong Mao, College of Engineering, China Agricultural University, China

Program and Technical Committee Members Professor Yanping Chen, University of Management and Technology, USA Professor Hongfeng Gao, University of California, USA Professor Michael Greenspan, Queen’s University, Canada Professor Birsen Donmez, University of Toronto, Canada Professor Xiangshi Ren, Kochi University of Technology, Japan Professor Kinhuat Low, Nanyang Technological University, Singapore Professor Baiqiao Huang, System Engineering Research Institute of China State Shipbuilding Corporation, China Professor Baoqing Xia, Weapon Industrial Hygiene Research Institute, China Professor Chenming Li, The Quartermaster Research Institute of Engineering and Technology, China

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Program and Technical Committee Information

Professor Fang Xie, China North Vehicle Research Institute, China Professor Guangtao Ma, Shenyang Jianzhu University, China Professor Haoting Liu, University of Science and Technology Beijing, China Professor Hongjun Xue, Northwestern Polytechnical University, China Professor Lijing Wang, Beijing University of Aeronautics and Astronautics, China Professor Long Ye, Beijing Jiaotong University, China Senior Engineer, Qichao Zhao, Beijing King Far Technology Co., Ltd., China Professor Qing Liu, Jinggangshan University, China Professor Weijun Chen, Shanghai Maritime University, China Professor Xiaochao Guo, The Fourth Military Medical University, China Professor Yongqing Hou, China Academy of Space Technology, China Professor Yanqi Wang, Weapon Industrial Hygiene Research Institute, China Professor Yinying Huang, Agricultural Bank of China, China Professor Yuhong Shen, The Quartermaster Research Institute of Engineering and Technology, China

Preface

In 1981, under the direction of the great scientist Xuesen Qian, an integrated frontier science—Man–Machine–Environment System Engineering (MMESE)— came into being in China. Xuesen Qian gave high praise to this emerging science. In the letter to Shengzhao Long, he pointed out, “You are creating this very important modern science and technology in China!” on October 22, 1993. In the congratulation letter to the commemoration meeting of the 20th anniversary of establishing the Man–Machine–Environment System Engineering, the great scientist Xuesen Qian stated, “You have made active development and exploration in this new emerging science of MMESE, and obtained encouraging achievements. I am sincerely pleased and hope you can do even more to make prosper development in the theory and application of MMESE, and make positive contribution to the progress of science and technology in China, and even in the whole world” on June 26, 2001. October 22, which is the day that the great scientist Xuesen Qian gave high praise to MMESE, was determined to be Foundation Commemoration Day of MMESE by the second conference of the 5th MMESE Committee on October 22, 2010. On this very special day, the great scientists Xuesen Qian pointed out in the letter to Shengzhao Long, “You are creating this very important modern science and technology in China!” The 19th International Conference on MMESE will be held in Shanghai, China, on October 19–21 of this year; hence, we will dedicate Man–Machine–Environment System Engineering: Proceedings of the 19th International Conference on MMESE to our readers. Man–Machine–Environment System Engineering: Proceedings of the 19th International Conference on MMESE is the academic showcases of the 19th International Conference on MMESE joint held by MMESE Committee of China and Beijing KeCui Academe of MMESE in Nanjing, China. The Man–Machine– Environment System Engineering: Proceedings of the 19th International Conference on MMESE consists of 102 more excellent papers selected from more than 500 papers. Due to limitations on space, some excellent papers have been left out, we feel deeply sorry for that. Crudeness in contents and possible incorrectness ix

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Preface

are inevitable due to the somewhat pressing editing time, we hope you kindly point them out promptly, and your valuable comments and suggestions are also welcomed. Man–Machine–Environment System Engineering: Proceedings of the 19th International Conference on MMESE will be published by Springer-Verlag, German. Springer-Verlag is also responsible for the related matters of index to EI, so that the world can know the research quality and development trend of MMESE theory and application. Therefore, the publication of Man–Machine–Environment System Engineering: Proceedings of the 19th International Conference on MMESE will greatly promote the vigorous development of MMESE in the world and realize the grand object of “making positive contribution to the progress of science and technology in China, and even in the whole world” proposed by Xuesen Qian. We would like to express our sincere thanks to Springer-Verlag, German, for their full support and help during the publishing process. Beijing, China July 2019

Prof. Shengzhao Long

Contents

Research on the Man Character Research on the Characteristics of Physical Fitness Testing for Special Operation Forces of Military Powers and Their Reference Value . . . . . Chunlai Wang Comparative Study of Acupuncture–Moxibustion and Transcranial Micro-Current Stimulation in Therapy of Altitude Hypoxia Headache and Insomnia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yongsheng Chen and Dalong Guo Scientific Data Sharing Platform Using Behavior Study Based on Extended TAM Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jianping Liu, Jian Wang, Guomin Zhou, Guilan Zhang, Yao Pan, Xu Sa and Tingting Liu

3

11

21

Subjectively and Objectively Measured Hazard Perception Ability of Young Chinese Drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Lingsen Hua, Long Sun and Yidan Ma

31

Experimental Research on Layout Accessibility of Individual Load-Carrying Equipment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yaping Wang and Shanlin ChenCai

37

Evaluation and Strategy Analysis of Students’ Mental Health in Semi-military Schools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Min Wang, Jintao Yu and Peng Wang

47

Study on Classification and Characteristic of Type of Lower Part of Body of Female College Students . . . . . . . . . . . . . . . . . . . . . . . . Jiandie Lin, Yuxiu Yan, Zimin Jin and Lu Lin

55

Correlation Study of Football Shin Guards Oppression and Muscle Fatigue During Sports . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yifei Mu, Zimin Jin, Jing Jin, Yuhan He and Yuxiu Yan

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Influence of Wristband Tightness on the Protection of Wrist Joint in Table Tennis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Mengyun Zhou, Zimin Jin, Jing Jin, Wenli Li and Yuxiu Yan

75

Optimal Design of the Elastic Unit for the Serial Elastic Hip Joint of the Lower Extremity Exoskeleton . . . . . . . . . . . . . . . . . . . . . . . . . . . Bingshan Hu, Guanming Cheng, Hongrun Lu and Hongliu Yu

85

Analysis About the Influence of Protective Equipment on the Upper Limbs’ Range of Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Chenming Li, Tianhao Wang and Yuhong Shen

95

Biomechanical Study of Long-Segment Spine Instrumentation: The Effect of Cross-Links . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Tianhao Wang, Chenming Li and Yan Wang Microexpression Recognition Training in Left-Behind Children in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Xueling Zhang, Lei Chen, Gaojie Fan, Huajie Sui and Xunbing Shen Research on the Relationship Between Personality and Speed Skills Training of Military Academy Cadets . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Nan Men, Qi Gong, Cheng Jin, Haitao Zhao, Pengdong Zhang and Zhibing Pang Research on Connection Between Physiological Index and Endurance Training on Military Academy Cadets . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Pengdong Zhang, Zhenyou Zhang, Xuechen Yao and Zhibing Pang Research on the Generation Law of Single-Machine Operation Skills . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Haitao Zhao, Cheng Jin, Xing Su, Genhua Qi and Zhibing Pang Eye Gaze Orientation and Pupil Size Variation on Time-Series Vigilance Task . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147 Deqian Zhang, Wenjiao Cheng and Hezhi Yang Research on Psychological Management of Officers and Men in MOOTW . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Zaochen Liu, Peng Gong, Yunqiang Xiang, Doudou Shan and Ailing Cheng The Influences of Capability and Character on Human’s Manual Dexterity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Shun Yao, Shengping Zhao and Zhongting Zhou Sniper Selection Index Measurement and Factor Weight Analysis . . . . . 169 Weiming Deng, Yubo Deng, Liwei Gong, Lu Hua, Shikun Wang and Fei Ji

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Investigation on the Index of Sniper Selection and Gray Correlation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177 Zhiwei Zhu, Weiming Deng, Bing Zhang, Shandong Mao and Chan Zhang Researches on the Eye-Movement Mode of Chinese College Students in Reading English Websites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Lijun Jiang, Bingbing Huang, Zhelin Li, Zhanghong Wu and Lu Lv Research on the Needs of Elderly Users of Electronic Sphygmomanometer Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Nan Li and Liqing Huang Analysis of Syncope Problem in Single Elderly and Application of Related Monitoring Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Chen Ni Physiological Measures of Mental Workload: Evidence from Empirical Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 Da Tao, Xu Zhang, Jian Cai, Haibo Tan, Xiaoyan Zhang and Tingru Zhang Ideological Method of Constructing Geometric Model of Human Heat Transfer Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Sina Dang, Hongjun Xue, Xiaoyan Zhang, Jue Qu, Chengwen Zhong and Siyu Chen Study of Correlation Between Subjective Symptoms and Ergonomic Load Index of Automobile Assembly Workers . . . . . . . . . . . . . . . . . . . . 235 Deshan Yin, Xiaofei Zhang, Yi Zhao and Shulin Zhou Research on the Machine Character Lane Detection Algorithm Based on Inverse Perspective Mapping . . . . . 247 Dong Chen, Zonghao Tian and Xiaolong Zhang A Preliminary Study on the Attractive Factors of Car Headlight Form Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257 Huan Lin, Shijian Luo, Chen Zhu, Hongzhuan Ding, Huiming Yi, Ze Bian and Fangtian Ying Design and Optimization of Command Software Interface . . . . . . . . . . . 265 Chunfeng Zhu, Danhua Sun, Zuohui Bao and XiaoFei Zhai A Subjective Assessment Method of Aerospace Image Quality Based on Human Visual System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Wuyuan Zhou, Haoting Liu, Chang Guo, Weidong Dong, Shuo Yang, Shunliang Pan and Guoliang Tian

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The Cabin Layout Project of the Ergonomic Evaluation Methods Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281 Sijuan Zheng, Li Li, Wenjun Guo, Fang Xie, Liang Ling and Zhongliang Wei Development of an Aviation Emergency Coping Ability Evaluation Instrument . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289 Qingfeng Liu, Yang Lv, Xiaochao Guo, Fei Peng, Yu Bai, Jian Du, Zhengtao Cao, Duanqin Xiong, Bo Gu and Yanyan Wang Developing Direction of Air Defense Electron-Magnetic Gun Based on Demand of Countering Air and Missile Threat . . . . . . . . . . . . 299 Jinxin Li, Yong Zhang, Guiqi Liu, Ruifeng Zhao, Tao Li and C. Mei The Integration Design Parameters Selection Method of Equipment Performance and Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307 Guanqian Deng, Suqiong Kuang, Yingjie Lv, Guiyou Hao, Shaojun Qi and Yuewen An The Integration Design Process and Method of Equipment Performance and Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 315 Guanqian Deng, Suqiong Kuang, Yingjie Lv, Guiyou Hao, Shaojun Qi and Pengjun Wang Design and Control of a Novel Pneumatic Soft Upper Limb Exoskeleton for Rehabilitation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321 Qiaoling Meng, Zhongzhe Chen, Yingchen Li, Zhenji Tian, Zhiyu Wu, Lei Li, Xi Tang and Xiao Cui Sketch Recognition and Interaction Design Based on Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 Wei Feng, WanFeng Mao, Baiqiao Huang, Guanqun Zhang, Pengyi Zhang, Xing Li, Jian Su and Xingjun Yuan Development and Application of Test Software of Fine Operation Ability of Directional Motion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339 Weicai Tang, Yi Xiao, Fenggang Xu and Chunhui Wang Research on Key Technology to Underwater Robotic Arm . . . . . . . . . . 347 Shang Huan, Suqin Wang, Xu Han and Jianzhi Bi A Portable Variable Stiffness Unpowered Aided Exoskeleton Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357 Luoqin Yu, Kai Wang and Tianning Chen Expressway Vehicle Management System Based on Vehicle Face Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369 Chan Zhang, Lijian Deng, Qicai Du and Weiming Deng

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The Research of Multilevel Takeover Alert Information Design for Highly Automated Driving Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . 377 Lijun Jiang, Simin Cao, Zhelin Li, Yu Zhang and Zequan Zhang Study on Application of Transfer Path on Micro-vibration Test for Satellite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 Gongbo Ma, Yao Wu, Dong Wang, Zhiyong Yue, Jiang Yang and Rui Wang Hierarchical Processing Model Based on Multi-modality Interaction Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395 Aiguo Lu, Bo Dong and Feiran Hu Application of Pipeline Ventilation Efficiency Test in Sanitary Ventilation Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 Huijun Zhang and Shulin Zhou The Influence on the Limit Flow Ratio Caused by the Change of the Area of the Exhaust Hood Face in the Design of Push–Pull Ventilation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417 Shulin Zhou, Bin Yang and Huijun Zhang Research on the Environment Character Simulation and Analysis of Sun Illumination on a Satellite . . . . . . . . . . 427 Na Zheng, Haoting Liu, Weidong Dong, Shuo Yang and Shunliang Pan Control Logic Design Based on Modeling of Aircraft Cockpit Temperature Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 435 Yudi Liu, Chengyun Wu, Zhiyong Min and Xuhan Zhang Simulation Method of Jamming Performance of Projectile-Carried Communication Jammer Based on OPNET Platform . . . . . . . . . . . . . . 445 Lizhi Qian, Jie Zhang and Dong Chen Experimental Study of Intelligent Lighting Control Method for Dark Field Surveillance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453 Haoting Liu, Chang Guo, Shuo Yang, Weidong Dong and Shunliang Pan Investigating the Comfort Distance of Chinese in Eight Directions . . . . 461 Xiaoqing Yu and Yu-Chi Lee Design and Application of a Ventilation System in a Washing Board Room Based on Numerical Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . 469 Bin Yang, Jianwu Chen, Shasha Liang, Shulin Zhou, Yanqiu Sun and Yunmeng Li

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Real-Time and Accurate Target Location Method Based on Artificial Mark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477 Qiaoling Meng, Haitao Wang, Hongliu Yu, Meng Wang and Bingshan Hu Modeling and Analysis of Fire Control Radar Capabilities Against Passive Jamming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 Wei Yu, Meng Kang, Xiaonian Wang, Jiang Luo and Yan Sun Inverse Design for Thermal Environment and Energy Consumption of Vehicular Cabins with PSO–CFD Method . . . . . . . . . . . . . . . . . . . . . 493 Zheming Tong, Hao Liu, Shuiguang Tong and Jiwang Xu Developing a Vehicle Thermal Management System with Fuzzy Control Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 503 Zheming Tong, Wenjun Shi, Shuiguang Tong and Yue Li Experimental Study on Color Requirements of Paratroopers for Transport Aircraft Cabin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513 Xiaochao Guo, Yanyan Wang, Jian Du, Yu Bai, Qingfeng Liu, Duanqin Xiong, Yu Duan, Qinglin Zhou, Wei Pan and Chunmei Gui Subjective Comprehensive Evaluation of LED Light Environment in Confined Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 521 Chuan Wang, Shenghang Xu, Guangjiang Wu, Jun Peng, Fenzhou Shi and Changbo Liao Quantitative Analysis of Relationship Between Subjective and Objective Evaluation Indexes of LED Light Environment in Confined Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531 Jian Zhang, Shenghang Xu, Jun Peng, Guangjiang Wu, Yang Yuan and Chuan Wang Complexity Assessment of Battlefield Electromagnetic Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541 Hongjun Cheng, Hao Jiang and Xujiao Wang Decompression Analysis for Maximum Effective Flow Area in Emergency Descent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549 Huayuan Liu and Shiquan Lin Diversification in Developing Lunar Dust Simulant . . . . . . . . . . . . . . . . 557 Hao Sun, Yao Wu, Jiang Yang, Rui Wang, Haiyang Gao and Yanjing Yang Design and Application of Test Process Management System for Spacecraft Vacuum Thermal Test . . . . . . . . . . . . . . . . . . . . . . . . . . 567 Xinming Su, Dongliang Wu, Zelin Fei, Jing Wang and Chang Liu

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Theory and Simulation Analysis of Acoustic Characteristics of a High-Level Traveling-Wave Acoustic Environment Simulation Device . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 577 Yao Wu, Zhiqiang Shen, Qiang Jiang, Guiqian Fang, Xinming Li, Jungang Zhang and Gongbo Ma Research on the Man-Machine Relationship Design of Central Console in Large Mining Excavator Based on Ergonomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591 Hongrui Zhang, Jiajun Ren, Aifeng Li and Jing Zhao The Influence of a Certain Type of Radar Operator’s Operating Ability on the Operational Effectiveness of Equipment . . . . . . . . . . . . . 599 Hongyan Ou, Di Wu, Lin Chen, Zhibing Pang, Zhiqinq Liu, Jifeng Wang, Jiantao Liu and Yan Xu Verifying Experimental Study on Colorful Display Schemes for See-through Display Information . . . . . . . . . . . . . . . . . . . . . . . . . . . 607 Duanqin Xiong, Wanli Lou, Qingfeng Liu, Yu Bai, Tao Jiang, Yanyan Wang, Jian Du, Fang Su, Cong Wang, Ke Jiang, Jing Huang, Qing He, Wen Dong and Xiaochao Guo A Software Approach of Human–Machine Interface Ergonomics Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617 Hongjun Xue, Ye Yuan, Jiayu Chen and Xiaoyan Zhang Ergonomics Evaluation of Cabin Human–Machine Interface Based on SHEL Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 623 Hongjun Xue, Jiayu Chen, Ye Yuan and Xiaoyan Zhang Study on Human–Machine Interface Design of Nuclear Power Plant Control Room . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 631 Shenghang Xu, Yiqian Wu and Chuan Wang Intelligent Human–Computer Interaction Design Based on Multi-modality Technology Applied to Shipborne Command and Control System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641 Aiguo Lu, Wen Li and Chao Pan Research on the Man-Environment Relationship Influence of Cut-in Situation on Driving Behavior of the Following Car Drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653 Fuwei Wu, Rui Fu, Xin Wang and Jinfeng Liu The Effect of Personal Protective Equipment on the Physiological Stress of Rescue Workers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 661 Tianhao Wang, Chenming Li and Yan Wang

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Plateau Environment’s Effects on College Students Psychological Health Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671 Yu Luo, Peijun Zheng, Zhenqin Wang, Yaqiong Chen and Xuechen Yao Research on Damage Mechanism of Projectile Fragments to Personnel Targets in Battlefield Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675 Yong Li Experimental Study on the Effect of Motion Sickness on 4D Movie Viewing Comfort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 685 Jinjin Wang and Zhengqing Jiang The Effects of Continuous Conversation and Task Complexity on Usability of an AI-Based Conversational Agent in Smart Home Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 695 Jingya Guo, Da Tao and Chen Yang Research on the Machine-Environment Relationship Electromagnetic Compatibility Design of a Certain Information System Command Vehicle in Complex Electromagnetic Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 707 Qiang Liu, Xiaofei Zhai, Zuohui Bao, Yangke Liu and Yong Wang Construction of Criterion for Applicability of Multi-mode Seeker to Complex Meteorology and Development of the Application Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 715 Shidong Fang, Dong Chen, Quanli Ning, Liang Ma and Junjian Li Research on the Overall Performance of Man-Machine-Environment System Practice and Research on the Modern Residential District Planning and Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 725 Zhen Li, Heng Chen and Fang Liu Ergonomics Analysis of Hand-Held Grinding Operation Working Posture Based on Jack . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 733 Yanqiu Sun, Jianwu Chen, Zhenlong Lu, Bin Yang and Weijiang Liu Establishment Methodology of Comfort Parameters Series for Civil Aircraft Cabin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 741 Xuhan Zhang, Chengyun Wu, Guangwen Wang and Xiaojin Xiao Determination of Fighter Cockpit DEP Based on WEPs of Pilots in Simulated Flight . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 751 Xiaochao Guo, Yanyan Wang, Yu Bai, Duanqin Xiong, Jian Du and Qingfeng Liu

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Fuel Gas Enterprise Accident Risk Assessment Based on BP Neural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 759 Qiquan Wang, Cheng Cheng, Chao Zhang, Jiahe Zhang and Kaiyuan Ning Digital Human Modeling for Performance Evaluation During Marine Vehicle Operation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 769 Yuan Liu, Tuoyang Zhou, Ning Li, Hao Li and Tiancheng Huang The Maintenance Control Logic Design of Virtual Maintenance Training System of a Certain Type of Equipment Based on Operation Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 779 Yong Wang, Fang Meng, Zuohui Bao, Hongtao Kan, Yangke Liu and Qiang Liu Research on the Management of Equipment Use Risk Based on “Man-Machine-Environment” Model . . . . . . . . . . . . . . . . . . . 787 Cheng Jin, Genhua Qi, Yao Xiao, Haitao Zhao, Zuohui Bao and Yu Luo Validation of Ergonomics Evaluation Method Based on Eye Tracking Technology in Unmanned Aerial System . . . . . . . . . . . . . . . . . . . . . . . . 793 Yanyan Wang, Bo Gu, Xiaochao Guo, Duanqin Xiong, Yu Bai, Jian Du and Qingfeng Liu Research on Essential Connotation of Military Management Revolution Centering on Effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . 803 Peng Gong, Dinghan Feng, Huiyong Wang and Ye Tao Research on the Safety Risk Management Model in Military Training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 811 Zhenguo Mei, Chang Mei, Peng Gong, Weifei Wu, Ye Tao and Wenying Xing Practical Significance, Main Problems, and Countermeasures of Safety Risk Management in Military Railway Transportation . . . . . . 819 Weifei Wu, Zhenguo Mei, Chang Mei, Peng Gong and Ye Tao Study on the Upper Flange Width on Grinding Worktable and Its Ergonomics Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 827 Jianwu Chen, Yanqiu Sun, Xiaolei Zhang, Zhenfang Chen, Bin Yang and Weijiang Liu A Linguistic 2-Tuple Multi-criteria Decision-Making Model for Military Training Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 837 Haiming Li, Gang Yu, Guobin Shang and Chongxin Tian The Mechanism of Servant Leadership on the Safety Performance of High-Speed Railway Drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 847 Long Ye, Zheng Yang and Ming Guo

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Research on Human–Machine Motion-Sensing Factors of Large VR Amusement Equipment Based on AHP Algorithm . . . . . . . . . . . . . . . . . 855 Wenxu Cong, Shaohua Wang and Zhengqing Jiang Study on Design of Vehicle Driver’s Control Area Based on Man-Machine System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 867 Tong Wu and Yuqi Yuan Usability Study of Signage Way-Finding System in Large Public Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 875 Jinxing Yang, Xinle Bao, Ying Zhu and Duming Wang Application of Virtual Human Factor Verification to Fire Accidents at the Main Control Room in Nuclear Power Plant . . . . . . . . . . . . . . . . 885 Zhiyao Liu, Qichao Zhao, Linwu Sun and Yantong Luo Theory and Application Research Base on Transportation and Separation of Municipal Solid Waste of Human-Machine-Environment System Research . . . . . . . . . . . . . . . . 895 Ziman Liu, Yuanchun Huang, Yifan Zhuang, Zhigang Liu and Xing Zhao Evaluation on the Man-Machine-Environment System of University Library . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 903 Kunzhu Zhang, Xinpo Wei, Quan Yuan and Jingyi Liu Human-Machine-Environment System Evaluation in Nuclear Power Plant Based on Virtual Reality Technology . . . . . . . . . . . . . . . . . . . . . . 913 Linwu Sun, Zhiyao Liu, Ming Jia and Qichao Zhao

About the Editors

Prof. Shengzhao Long is Founder of the Man–Machine–Environment System Engineering (MMESE), Chairman of the Man–Machine–Environment System Engineering (MMESE) Committee of China, Chairman of the Beijing KeCui Academe of Man–Machine–Environment System Engineering (MMESE) and Former Director of Ergonomics Lab of Astronaut Research and Training Center of China. In October 1992, he is honored by the National Government Specific Allowance. He graduated from the Shanghai Science and Technology University in 1965, China. In 1981, directing under famous Scientist Xuesen Qian, he founded MMESE theory. In 1982, he proposed and developed human fuzzy control model using fuzzy mathematics. From August 1986 to August 1987, he conducted research in man–machine system as Visiting Scholar at Tufts University, Massachusetts, USA. In 1993, he organized Man–Machine–Environment System Engineering (MMESE) Committee of China. He published “Foundation of theory and application of Man–Machine–Environment System Engineering” (2004) and “Man–Machine–Environment System Engineering” (1987). He edited “Proceedings of the 1st–18th Conference on Man–Machine–Environment System Engineering” (1993–2018). e-mail: [email protected] Dr. Balbir S. Dhillon is Professor of engineering management in the Department of Mechanical Engineering at the University of Ottawa, Canada. He has served as Chairman/Director of Mechanical Engineering Department/Engineering Management Program for over 10 years at the same institution. He has published over 345 (i.e., 201 journals + 144 conference proceedings) articles on reliability, safety, engineering management, etc. He is or has been on the editorial boards of nine international scientific journals. In addition, he has written 34 books on various aspects of reliability, design, safety, quality and engineering management published by Wiley (1981), Van Nostrand (1982), Butterworth (1983), Marcel Dekker (1984), Pergamon (1986), etc. His books are being used in over 85 countries, and many of them are translated into languages such as German, Russian and Chinese. He has

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About the Editors

served as General Chairman of two international conferences on reliability and quality control held in Los Angeles and Paris in 1987. He has served as a consultant to various organizations and bodies and has many years of experience in the industrial sector. At the University of Ottawa, he has been teaching reliability, quality, engineering management, design and related areas for over 29 years and he has also lectured in over 50 countries, including keynote addresses at various international scientific conferences held in North America, Europe, Asia and Africa. In March 2004, he was a distinguished speaker at the Conference/Workshop on Surgical Errors (sponsored by White House Health and Safety Committee and Pentagon), held at the Capitol Hill (One Constitution Avenue, Washington, D.C.). He attended the University of Wales where he received a BS in electrical and electronic engineering and an MS in mechanical engineering. He received a Ph.D. in industrial engineering from the University of Windsor. e-mail: dhillon@genie. uottawa.ca

Research on the Man Character

Research on the Characteristics of Physical Fitness Testing for Special Operation Forces of Military Powers and Their Reference Value Chunlai Wang

Abstract This paper studies different contents of physical fitness testing of special forces of military powers by using the methods of documentation and case study and analyses the characteristics and general rules of physical fitness training of foreign special forces. The results show that the long-term practical experience accumulated by foreign special forces is the precondition for setting strict physical fitness test subjects. The selection of physical fitness test means has strong pertinence and practicability, which meets the specific needs of special forces in carrying out combat tasks. It is concluded that the physical fitness test of PLA special forces should gradually develop toward (1) affirming the practical value of functional training to realize training functionalization; (2) establishing digital platform for special operations training to realize training informatization; (3) promoting the establishment of special operations base training model to realize training systematization. Keywords Special operation forces Reference value


Physical fitness testing
Characteristic


1 Foreword Special operations require unique modes of employment, tactics, techniques, procedures, and equipment. They are often conducted in hostile, denied, or politically and/or diplomatically sensitive environments and are characterized by one or more of the following: time sensitivity, clandestine or covert nature, low visibility, work with or through indigenous forces, greater requirements for regional orientation and cultural expertise, and a higher degree of risk.

C. Wang (&) Physical Education Department, Guangzhou University Sontan College, 511370 Guangzhou, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_1

3

4

C. Wang

Therefore, it is the general consensus of all countries to follow the principle of demanding training for special forces. And the test standard of basic quality can best embody this principle. Basic quality is not only the basis of military skills training, but also the main means of physical fitness testing. However, the contents of physical fitness tests of special forces in different countries are not exactly the same due to different historical experiences.

2 Objective The abundant practical experience of foreign special forces is the baton to change the content and standard of physical fitness test (PFT). Therefore, its physical fitness test should have strong pertinence and practicability. While our army has also established special forces with the development of the times, the understanding of its basic physical training is relatively backward due to the lack of cross-border experience in carrying out special military tasks and the lack of innovative theoretical support. The purpose of this study is to borrow ideas by matching the military powers in the field of physical fitness testing of Special Operation Forces (SOF), giving support to renew the training concept and to innovate the training theory of PLA Special Operation Forces.

3 Methods This paper, by using the literature research method and case study approach, studies the characters of physical fitness test and standards of representative special forces of military powers, such as the US Navy Seals, the British Special Air Service, and the Canadian Joint Task Force 2. Summarize the general rules of physical fitness test.

4 Procedures 4.1

Physical Screening Test of US Navy SEALs

Unlike other special forces, the US special forces, especially the US Navy Seals, have a wealth of practical experience. From the starts of naval special warfare during World War II to the killing of Osama bin Laden, about ten important events and operations in the history of the US Navy SEALs are worthy of attention. They are in Table 1.

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Table 1 Major mission by SOF from 1944 to 2012 No.

Year

Mission

1 1944 D-Day Landings 2 1945 Invasion of Okinawa 3 1965–72 Vietnam War 4 1983 Invasion of Grenada 5 1989 Capture and arrest of Manuel Noriega 6 1991 Operation Desert Shield and Desert Storm 7 2005 Operation Red Wings 8 2009 Rescue of Captain Richard Phillips from Somali pirates 9 2011 Killing of Osama bin Laden (Operation Neptune Spear) 10 2012 Rescue of aid workers in Somalia Source https://www.history.com/news/navy-seals-10-key-missions

The US Navy SEALs were created by Presidential Order on January 8, 1962, by then President John F. Kennedy. The original intended purpose of the SEALs was to conduct military operations in maritime and riverine environments. After drawing lessons from Operation Desert One in 1980 in Iran and Operation Urgent Fury in Grenada in 1983, Naval Special Warfare Forces are gradually tasked with multi-component missions. They are in Table 2. A potential candidate for the US Navy SEAL training must meet rigorous physical and mental requirements and then is assessed through SEAL Physical Screening Test (PST). See Table 3. Table 2 Core activities for US Navy SEALs Number

Original mission

1 2 3

Military operations in maritime and riverine environments

Present mission

Direct action Special reconnaissance Countering weapons of mass destruction 4 Counterterrorism 5 Unconventional warfare 6 Foreign internal defense 7 Security force assistance 8 Hostage rescue and recovery 9 Counterinsurgency 10 Foreign humanitarian assistance 11 Military information support operations 12 Civil affairs operations Adapted from https://bootcampmilitaryfitnessinstitute.com/elite-special-forces/us-elite-specialforces/navspecwarcom-us-naval-special-warfare-command-nswc/us-naval-special-warfare-operat or-aka-us-navy-seal-selection-training/

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Table 3 US Navy SEAL physical screening test Requirements (PST) PST

Minimum

SWIM 500YDS. Side stroke/breast stroke 12:30 min/sec PUSH-UPS (within 2 min) 42 SIT-UPS (within 2 min) 50 PULL-UPS (no time limit) 6 1.5 MILE RUN 11:00 min/sec PST Score 1220 Source https://navyseals.com/nsw/physical-screening-tests/

Competitive 10:30 min/sec 79 79 11 10:20 min/sec 827

Candidates with a PST score of 827 or less are much more likely to be selected for a US Navy SEAL contract and consequently more likely to successfully complete US Navy SEAL training.

4.2

The British Commandos Test

Special Air Service (SAS), which primary mission is to carry out raids, has carried out many special operations in foreign territories after World War II. They are in Table 4. Table 4 Known postwar operations list of SAS 1950s–1970s (the Cold War) 1

1980s–1990s

2000s–2010s (The War on Terror)

Operation Operation Nimrod Operation Enduring Freedom Helsby Iranian Embassy Siege War in Afghanistan Malayan Emergency 2 Jebel Akhdar Operation Corporate Operation Telic War Falklands War Iraq War 3 Operation Operation Banner Operation Enduring Freedom Claret The Troubles Horn of Africa Indonesian Confrontation 4 Keeni-Meeni Operation Granby Operation Ellamy Operations Persian Gulf War Libyan Civil War Aden Emergency 5 Operation Operation Joint Endeavor Operation Shader against the Storm Bosnian War Islamic State of Iraq and the Dhofar Levant Rebellion 6 Operation Operation Chavín de Huántar Feuerzauber Japanese embassy hostage crisis Lufthansa Flight 181 Adapted from https://en.wikipedia.org/wiki/List_of_SAS_operations

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Table 5 Test of All Arms Commando Course

1

Test event

Minimum requirement in 1960s

Arms weight (kg)

Speed March

Six-mile (9.65 km) in 60 min Four-mile (6.4 km) run within 80 min Over varying obstacles in 5 min

13.6

Minimum requirement in 2013

Arms weight (kg)

9 mile (14.5 km) in 13.6 90 min 2 Endurance 13.6 10 mile (16 km) run 13.6 Course within 73 min 3 Tarzan Assault 13.6 Over varying 13.6 Course obstacles in 12.5 min 4 Cross-country Twelve-mile 40.8 30-mile (48.2 km) 40.8 March (19.3 km) in 7 h Adapted from https://bootcampmilitaryfitnessinstitute.com/elite-special-forces/uk-elite-specialforces/aacc-all-arms-commando-course-overview/

Now, the All Arms Commando Course (AACC) is designed for the selection of SAS candidates and aims to seek the development, to the very highest possible degree, of stamina and endurance under any operating conditions and in all types of environment. It aims to perfect all individuals in every basic military requirement, as well as in the special work likely to be encountered in operations in and outside the territories. Success on the course entitles the candidate to wear the commando green beret. The commandos’ tests, in which each commando trainee would be carrying a rifle (4.1 kg) and equipment (9.5 kg), are the final proof that individuals are ready for their green beret and to start their career as a SAS Commando. With the passage of time and the accumulation of overseas practical experience, the content and intensity of the test have increased significantly (Table 5).

4.3

Canadian Assaulter Pre-selection Physical Fitness Testing

Canadian SOF named Join Task Force 2(JTF 2), which was established as a hostage rescue unit, was created in 1986. Its first appearance outside of Canadian SOF was participating in Operation Enduring Freedom to support the American action in Afghanistan from December 2001 to November 2002 after 9/11. Unquestionably, JTF2’s participation in Operation Enduring Freedom (OEF) was a critical turning point in its evolution and CANSOF history. Since then, JTF 2 became a pure counterterrorism unit [1].

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Special Operations Assaulter Pre-selection Physical Fitness Test Program for JTF2 was developed by the Canadian Forces Morale and Warfare Services, Directorate of Fitness, in conjunction with the Canadian Special Operations Forces Command. And the physical fitness components are necessary for the successful selection which are included below (Table 6). “Recruits run a gauntlet of scientifically designed physical and psychological tests. Typically, only two in 10 soldiers who train for the unit succeed in becoming ‘assaulters,’ a position that can pay a premium six-figure salary” [2]. And the testing requires far greater expenditure of physical energy than is normally required in other peacetime training. Soldiers were required to meet the minimum score of 75 can pass the exam. See Table 7.

Table 6 Physical fitness components Fitness component

Event

1 Aerobic power (VO2max) 2400 m run 2 Aerobic capacity 8 km run 3 Anaerobic capacity 400 m run 4 Upper body strength Bench press, push-ups, pull-ups 5 Lower body strength Squats 6 Abdominal strength Sit-ups 7 Lower body power Vertical jump 8 Lower body speed 40 m sprint Adapted from Wenger, H., Jaenen, S. & Carlson, M. (2015) SOA: Special Operations Assaulter Pre-Selection Physical Fitness Training Programme. p. 24

Table 7 Partial standard for SOF physical fitness test Score (points)

1.5 mile run (min/sec)

Push-ups (#continuous)

Sit-ups (#in 60 s)

Pull-ups (# continuous)

1 RM bench press (kg)

11 09:45–09:40 40–41 40–41 5 65 12 09:39–09:34 42–43 42–43 6 70 13 09:33–09:28 44–45 44–45 7 75 14 09:27–09:22 46–47 46–47 8 80 15 09:21–09:16 48–49 48–49 9 85 16 09:15–09:10 50–51 50–51 10 90 17 09:45–09:40 52–53 52–53 11 95 Source https://www.cfmws.com/en/AboutUs/PSP/DFIT/Fitness/Pages/Joint-Task-Force-Two(JTF-2).aspx Joint Task Force 2 (JTF 2) Pre-Selection Physical Fitness Evaluation

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5 Conclusion 5.1

Affirming the Practical Value of Functional Training

“Compared with traditional physical training, functional training emphasizes the accuracy and stability of training action, aiming at improving training efficiency and preventing sports injury” [3]. For example, push-ups are one of the basic performance test items. If the standardization of the basic posture and the correctness of the movements were not be emphasized, excessive use of compensatory movements such as waist piercing will cause fatigue accumulation in the short-term and long-term waist strain. Such training greatly reduces the training value of push-ups themselves. And “strength quality is the basis for a special soldier to perform various movements reasonably and efficiently” [4]. Attaching importance to core strength training can improve training performance and reduce limb joint injury. For example, recruits are feeling weak when throwing a bomb, and creeping forward or poor 100 m sprint results, one of the main reasons is the lack of core strength.

5.2

Establishment of Digital Platform for Special Operations Training

In order to realize the digitalization and informatization of physical training information collection and evaluation, the digital physical fitness testing and evaluation system and personal physical training files of special operations soldiers should be perfected and popularized in the whole army. At the same time, “the evaluation mechanism of results publication, summary, and training report should be standardized, so as to grasp more accurately the development of physical training of special forces and scientifically evaluate the physical condition of special forces and individual soldiers in special operations” [5].

5.3

Promoting the Establishment of Special Operations Base Training Model

The army will vigorously promote the implementation of the training mode of special operations bases, incorporate the renewal of weapons and equipment, introduce the main battle equipment and simulation training equipment of the army, and build a new simulation training center for the operational units of the armed forces, so as to form a simulation training equipment system covering the fields of skills, command, and tactics.

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“Expanding the frequency of joint training linked to the military training bases of the friendly and neighboring forces and gradually building a training base system that is consistent with the operational tasks and adapts to the basic operational modes” [6].

References 1. Horn B (2012) “We will find a way”: understanding the legacy of Canadian special operations forces. JSOU Report 12-2. February 2012. Available from World Wide Web: http://jsou. socom.mil/JSOU%20Publications/12-2_Hom_CanadianSOF(Febl2)_final.PDF. Accessed 17 Apr 2016 2. Freeze C (2010) Silent killers: secrecy, security and JTF2. Available from World Wide Web: http://www.theglobeandmail.com/news/national/silent-killers-secrecy-security-and-jtf2/ artidel319588/. Accessed 17 Apr 2016 3. Yan Z (2012) The application of functional training in U.S Army physical training and its enlightenment for PLA. J PLA Inst Phys Educ 31(2):78–80 4. Zhu H, Zhang Y, Li F (2004) The demand of the soldier physical force on the synthesis drilling in the special type army. J PLA Inst Phys Educ 23(3):107–109 5. Chen Y (2013) Study and thought of physical fitness training in US and Russian army. J Mil Phys Educ Sports 32(3):23–26 6. Tan B (2018) Innovatively employing simulated, networked and base training modes to continuously improve the troops training and readiness in the new era. The Defence 03:5–7

Comparative Study of Acupuncture–Moxibustion and Transcranial Micro-Current Stimulation in Therapy of Altitude Hypoxia Headache and Insomnia Yongsheng Chen and Dalong Guo

Abstract Objective Comparison of the influence of acupuncture–moxibustion (AM) and transcranial micro-current stimulation (TMCS) on altitude hypoxia headache and insomnia. Methods Eighty military persons suffering headache and insomnia (40 were divided into plain group or control group, 20 of 40 were divided into AM control group, and the others were divided into TMCS control group; 40 were divided into altitude group, 20 of 40 were divided into altitude AM group, and the others were divided into altitude TMCS group) were cured by AM and TMCS technology, respectively. Treatment effect was compared to each other. Results The effecient were 75% by using TMCS to reduce headache and insomnia in altitude, that in using AM were 70%, which effect of this two technology were no significant change. Conclusions The same as AM, TMCS can effectively reduce hypoxia headache and insomnia residing altitude for a long time and provide a useful tool and methodology for altitude military medical service.




Keywords Altitude Transcranial micro-current stimulation Acupuncture–moxibustion Hypoxia Headache Insomnia Cerebral function Military medical service

















1 Introduction Headache and insomnia caused by altitude hypoxia are the most common brain dysfunction among those who enter the plateau for the first time. Although taking drugs to improve the metabolism of red blood cells, such as acetazolamide and

Y. Chen
D. Guo (&) Air Force Medical Center, PLA, Beijing 100142, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_2

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rhodiopsis rosea, or directly taking oxygen can also improve the above symptoms, they all indirectly improve the brain function, and the after-effects of drugs can easily affect military operations [1–4]. It has been reported in the literature that the treatment of headache and insomnia with acupuncture–moxibustion (AM) has been used for over half a century in domestic clinical treatment, and the efficacy is positive [5, 6]. AM technology is based on the principle of traditional Chinese medicine “meridian,” in the treatment of some symptoms (such as headache and insomnia) related to the skull “acupoints” to apply needle stimulation so that the needle is feeling acid, numbness, distension, pain, that is, “qi” and to improve symptoms and treatment purposes. However, transcranial micro-current stimulation (TMCS) technology directly affects the central nervous system of the brain through scalp electrodes, acts on the brain nerve tissue through the additional electric field simulating brain waves, regulates the metabolism of neurotransmitters and the potential level of nerve cell membrane, so as to improve the abnormal state of brain functions such as headache and insomnia [7–9]. Both techniques, though used in different ways, exert an influence on the nervous system. Clinical AM technology needs to be applied to the patient lying on his back, the doctor on his body, during the needle, cannot carry out any activities unrelated to the needle; therefore, the technology for the purpose of military service support for the general military personnel has a lot of restrictions and inconvenience. However, TMCS technology is non-invasive and can be developed into portable devices, and the treatment (or guarantee) period is not limited by time, place, and conditions. In this study, by comparing the differences in the treatment effects of these two technologies on plateau headache and insomnia, an optional technical means was provided for the plateau health service guarantee.

2 Subjects and Methods 2.1

Subject and Grouping

A self-designed questionnaire was used to screen out 40 volunteers (aged 24– 40 years old, male, without plateau life history and generally healthy) with poor sleep quality (insomnia) as users in the plain (low-altitude group), including 20 in the AM control group and 20 in the TMCS control group. A total of 40 volunteers with the same symptoms (aged 24–40 years old, male, no plateau life history, and generally healthy) were selected as plateau users using the same questionnaire in the plateau (high-altitude group, the environmental altitude was more than 3700 m), among which 20 were in the AM treatment group and 20 were in the TMCS group.

Comparative Study of Acupuncture–Moxibustion …

2.2 2.2.1

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Method Medical Instruments and Equipment

(1) Tools for AM using clinical head face special needles of traditional Chinese medicine acupuncture (ZB—1, suzhou medical supplies factory co., LTD., registration number: Sue food drug safety machinery (quasi) words: 2012 No. 2270932), (2) TMCS process to use plateau portable brain function adjusting device (TMCS based technology, models BT701-1 a, Shanghai huayi medical instrument co., LTD., registration number: Shanghai food drug safety machinery (quasi) words: 2009 no. 2271502).

2.2.2

Treatment Process

(1) AM treatment: Subjects were needled spell to the “temple,” “Fengchi” four special acupoints on the left or right hemisphere, respectively, by experienced physicians according to the clinical treatment of acupuncture specification, which those had mild acid, numbness, distension, and pain feeling (or qi) for AM work. Treated 30 min every day, lasted 1 month. (2) TMCS treatment: Using plateau portable brain function adjusting device with AM same acupoint put stimulating electrode, using a 0–40 Hz frequency, pulse width of 0.5 ms asymmetric continuous wave bi-directional pulse on head acupoint electrical stimulation (2–4, 7–9), receiving treatment for 15 min every day, 15 days for a period of treatment, continuous two courses of treatment (1 month). (3) Experimental procedures: the treatment of AM and TMCS in the low-altitude group and the high-altitude group was divided into two stages: plain low-altitude region (control data obtained) and plateau region. The treatment effect of AM or TMCS (one course) was evaluated by users through a self-designed questionnaire.

2.2.3

Methods of Efficacy Evaluation

(1) Subjective questionnaire survey: the efficacy of the treatment method was evaluated by the user based on a self-designed questionnaire (the degree of treatment comfort was rated as 2 points according to “perceived comfort”; 1 for “relatively comfortable”; “Poor comfort” rated 0). Headache plus insomnia symptom improvement effect (improvement degree, according to “obvious improvement effect” as 2 points; 1 for “average improvement effect”; “No improvement effect” rated as 0 points). (2) Sleep quality assessment: the Pitsburgh sleep quality index (PSQI) was used to evaluate the sleep quality after the plateau resident treatment, including subjective sleep quality, sleep time, sleep efficiency, sleep disorder,

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hypnotic drug application, and daytime dysfunction. Each item is scored on a scale of 0, 1, 2, 3, with a total score ranging from 0 to 21. The higher the score, the worse the sleep quality.

2.2.4

Statistical Analysis

Score the items in the recovered self-rating scale, calculate the percentage, and use X2 test to compare the rates (%). P < 0.05 is considered statistically significant.

3 Results 3.1

AM and TMCS Comfort Survey

80 questionnaires were issued, and 80 were recovered; the recovery rate was 100%. In the AM group, 4 people answered “feel comfortable”, 2 people answered “relatively comfortable”, and 34 people answered “poor comfort.” The comfort evaluation rate of AM method is 10% (4/40). In the TMCS group, 35 people answered “feel comfortable”, 5 people answered “relatively comfortable”, and 0 people answered “poor comfort.” The comfort evaluation rate of the TMCS method was 87.5% (35/40), and the comfort level of the TMCS method was much higher than that of the AM method.

3.2

Treatment Effect of Headache and Insomnia

A total of 80 questionnaires were distributed to investigate the treatment effect of headache and insomnia, and 80 were recovered, with a recovery rate of 100%.

3.2.1

AM Treatment Effect Survey

In plain area, 9 people answered “obvious improvement effect of insomnia,” 6people answered “moderate improvement effect of insomnia,” 5 people answered “no improvement effect of insomnia;” the improvement effect of insomnia was 45% (9/20), the improvement effect of insomnia was 30% (6/20), and the improvement of insomnia inefficiency was 25% (5/20). Plateau answer “insomnia headache plus improve obviously” 14 people, answer “insomnia headache plus improvement effect generally” item 4, answer “headache plus insomnia without improvements” item 2 people, improve insomnia headache plus effect rate was 70% (14/20), obviously improve insomnia headache plus effect generally 20% (4/20), improve insomnia headache plus efficiency is 10% (2/20).

Comparative Study of Acupuncture–Moxibustion …

3.2.2

15

TMCS Treatment Effect Survey

In plain area, 8 people answered “obvious improvement effect of insomnia,” 8 people answered “moderate improvement effect of insomnia,” and 4 people answered “no improvement effect of insomnia.” The significant rate of improvement effect of insomnia was 40% (8/20), general improvement effect of insomnia was 40% (8/20), and improvement effect of insomnia was 20% (4/20). Plateau answer “insomnia headache plus improve obviously” item of 15 people, answer “insomnia headache plus improvement effect generally” item 3 people, the answer “plus headache insomnia without improvements” item 2 people, improve insomnia headache plus effect rate was 75% (15/20), obviously improve insomnia headache plus effect generally 15% (3/20), improvement of insomnia headache plus 10% (2/20) inefficiency, as shown in Table 1. Comparison of application effects in different altitudes shows that AM method and TMCS method are more effective in plateau areas than in plain areas, and both methods can effectively improve oxygen-deficient headache and insomnia symptoms in plateau areas without significant difference. After one course of treatment (1 month), both AM and TMCS methods improved the subjects’ sleep quality in the plateau area, and there was no significant difference between the two technologies, as shown in Table 2.

4 Discussion 4.1

AM and TMCS May Act on Human Body Through the Same Neural Pathway

AM physical process is in the human body surface “acupuncture point” on the needle, through twist, pressure silver needle (into the needle), let subject feeling acid, hemp, distension, pain, to regulate the meridian system and achieve the purpose of intervention of various symptoms [5]. TMCS technology uses scalp electrodes to introduce micro-current, which directly acts on the central nervous system of the brain, by simulating the additional electric field of brain waves, it acts on the nervous tissue of the brain, regulates the metabolism of neurotransmitters, and changes the potential level of nerve cell membrane to improve the abnormal state of brain functions such as headache and insomnia [7–11]. Neurophysiology of AM and TMCS technology basis included peripheral nervous system, composed of the nervous system and autonomic nervous system including somatic sensory nerve fibers in the nervous system can be collected by all parts of the body sense organs such as pain, touch to convey information to the brain or spinal cord, make the person of acid, hemp, bilge, pain feeling; Motor fibers, on the other hand, are responsible for transmitting the central nervous system’s integrated analysis of acid, numbness, distension, and pain to skeletal muscles to generate corresponding limb

AM Symptom improvement significant s Symptom improvement general

No improvement effect

Plain (insomnia) 45.0 (9/20) 30.0 (6/20) 25.0 (5/20) Plateau area 70.0 (14/20)a 20.0 (4/20)a 10.0 (2/20)a (headache + insomnia) X2 23.38 23.15 15.00 P LVC?) PU

0.826 0.674

INT

0.873

Yes Yes Yes Yes Yes Yes

The Structural Model

The structural model is also evaluated by PLS-SEM algorithm and SmarPLS3 statistical software [6]. The main measurement indexes of the structural model are R2 and composite-based standardized root-mean-square residual (SRMR). R2 represents the explanatory power of the model (e.g.,, R2B ¼ 0:613 in this study, which indicates that the model explains 61.3% of the actual behavior), the value is 0–1, and the minimum value shall not be less than 0.1. SRMR represents the overall fitting degree of the model, the smaller the better; it is generally not more than 0.1 [9]. As shown in Table 4, R2 and SRMR both meet the requirements. The significance level of path coefficient reflects the relationship strength between latent variables. In this study, bootstrap techniques in Smartpls3 are used (suggested setting: 5000 bootstrap samples; no sign changes) to evaluate the path coefficient and its significance [10]. As shown in Table 4, the research hypotheses H1–H9 are all valid. Table 4 Results of hypothesis testing Hypothesis

Relationships

Path coefficient

T-value

PEOU ! PP 0.516*** 11.937 *** 5.289 PEOU ! ATT 0.267 22.277 PEO ! PU 0.662*** PP ! ATT 0.054 1.039 PP ! INT 0.200** 3.689 9.060 PU ! ATT 0.525*** 3.462 PU ! INT 0.249*** 5.870 ATT ! INT 0.390*** 29.851 INT ! B 0.783*** SRMR = 0.049; R2B ¼ 0:613; R2INT ¼ 0:552; R2ATT ¼ 0:591; R2PU ¼ 0:439; R2PP *** Note represents significant at p < 0.001 (two-tailed) H1 H2 H3 H4 H5 H6 H7 H8 H9

Supported Yes Yes Yes No Yes Yes Yes Yes

¼ 0:266

Scientific Data Sharing Platform Using Behavior Study …

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5 Conclusions The behavior attitude of users’ scientific data sharing platform is mainly influenced by perceived ease of use, perceived usefulness, and perceived playfulness. At the same time, user’s behavior intention of scientific data sharing platform is influenced by user’s behavior attitude, perceived usefulness, and perceived ease of use. These factors can be divided into two categories: intrinsic and extrinsic. Perceived ease of use and perceived usefulness belong to extrinsic. Perceived pleasure, behavior attitude, and behavior intention belong to intrinsic. If the scientific data retrieval and sharing platform can comprehensively consider the intrinsic and extrinsic factors that affect the use of user systems, then the use efficiency of the system will be greatly improved.

6 Implications 6.1

Implications for Man–Machine Interaction

Scientific data users use scientific data sharing platform to query and retrieve data is a typical human–computer interaction behavior. Based on the research results of this study, it is believed that the human–computer interaction should adhere to the human-centered principle, continuously improve the “harmonious” state between the system and human, and finally achieve the efficient combination of human and system. In this study, the focus is on the psychological factors that affect users’ behavior. Through verification, it is found that the core influencing factors are perceived usefulness and behavior attitude. This conclusion can be used as an important basis to improve the efficiency of human–computer interaction in scientific data query and retrieval.

6.2

Implications for Data Platform Design

The design and improvement of scientific data sharing platform should follow the principles of simplicity and usefulness. In this study, perceived ease of use refers to the user’s perception of the difficulty of system functions. The path coefficients of perceived ease of use to behavioral attitude, perceived playfulness, and perceived usefulness are 0.267, 0.516, and 0.662, respectively, which have significant influence. At the same time, perceived usefulness has significant influence on behavior attitude and behavior intention, with path coefficients of 0.525 and 0.249, respectively. Perceived usefulness explains the user’s perception of the system’s function and value. Perceptual ease of use and perceived usefulness reveal extrinsic factors that affect users’ use of scientific data sharing platforms.

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7 Limitations and Future Work The research still has the following limitations: first, lack of human–computer interaction experiments. In the future, the research results will be further optimized by combining eye-tracking experiments and user interviews. Second, the research is not representative enough. The subjects were mainly master’s and doctoral students. Future research will further expand the research object and make the research more representative. Acknowledgements This work was supported by a grant from Social science fund—Scientific Data User Relevance Criteria and Use Model Empirical Study (14BTQ056), and National High-tech R&D Program of China (863 Program No.2013AA102405) and Agricultural Science, Technology Innovation Project of Chinese Academy of Agricultural Sciences (Project No. CAAS-ASTIP-2016-AII). Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Agricultural Information Institute, Chinese Academy of Agricultural Sciences. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Stevens H (2016) Big data, little data, no data: scholarship in the networked world by christine l. borgman (review). J Assoc Inf Sci Technol 67(3):751–753 2. Brynjolfsson E (1993) The productivity paradox of information technology. Commun ACM 36(12):66–77 3. Davis FD (1985) A technology acceptance model for empirically testing new end-user information systems: theory and results. J Multivar Anal 4. Fishbein M, Ajzen I (1977) Belief, attitude, intention, and behavior: an introduction to theory and research. Contemp Sociol 6(2) 5. Moon JW, Kim YG (2001) Extending the tam for a world-wide-web context. Inf Manage 38 (4):217–230 6. Ringle CM,Wende S, Becker JM (2015) Smart PLS 3. Boenningstedt: SmartPLS GmbH. Available online at: Retrieved from http://www.smartpls.com 7. Hair JF, Ringle CM, Sarstedt M (2011) Pls-sem: indeed a silver bullet. J Mark Theor Pract 19 (2):139–152 8. Larcker FDF (1981) Evaluating structural equation models with unobservable variables and measurement error. J Mark Res 18(1):39–50 9. Henseler Jörg, Ringle CM, Sarstedt M (2015) A new criterion for assessing discriminant validity in variance-based structural equation modeling. J Acad Mark Sci 43(1):115–135 10. Nevitt J, Hancock GR (2001) Performance of bootstrapping approaches to model test statistics and parameter standard error estimation in structural equation modeling. Struct Equ Model 8(3):353–377

Subjectively and Objectively Measured Hazard Perception Ability of Young Chinese Drivers Lingsen Hua, Long Sun and Yidan Ma

Abstract The present study examined the characteristics of subjectively and objectively measured hazard perception ability of violation-free and violationinvolved drivers and the consistency between self-assessments and their response time. Forty-seven young Chinese novice drivers finished a video-based hazard perception task and a self-reported hazard perception questionnaire. Results showed that violation-free drivers responded to the hazards faster than violation-involved drivers. Violation-free drivers also had lower self-assessment score than violationinvolved drivers. Importantly, drivers’ self-assessment score correlated positively with the number of traffic violations from the last year. No significant correlations were found between drivers’ response time to the hazards with their selfassessments or the number of traffic violations. The findings suggested that young drivers’ self-assessments did not correspond to their response time, which might partially contribute to their violation involvement. Keywords Hazard perception time Traffic violations





Young drivers
Self-assessment
Response

1 Introduction Among the factors that attributed to young novice drivers’ accident involvement, hazard perception ability has been proved to be a key factor. Hazard perception refers to drivers’ ability to identify hazard on the road [1]. Many studies have reported that young novice drivers’ slower response time was associated with their accident involvement [2, 3]. Despite of lack of driving experience, young novice drivers’ inaccurate estimation of their hazard perception ability also played an important role in determining their response time [4]. L. Hua
L. Sun (&)
Y. Ma School of Psychology, Liaoning Normal University, Shahekou District, Huanghe Road. 850, 116029 Dalian, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_4

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Previous studies have found the young novice drivers often rated themselves superior to their peers when it comes to hazard perception ability [5]. This might pose an adverse impact on their detection and response to the hazards in real driving. However, regarding the relationship between young drivers’ response time to the hazards and their self-assessed hazard perception ability, mixed results were reported. Some studies have reported that young novice drivers’ self-assessments did not correspond to their performance in a driving simulator [6] or in a video-based hazard perception task [7]. However, the findings of a recent study show that young male drivers’ self-assessment corresponded to their response time to overt hazards in a driving simulator [4]. Given the inconsistency, the present study will further examine the consistency of subjective and objective measured hazard perception ability using a video-based hazard perception task. Another concern in the literature was whether violation-free drivers differ from violation-involved drivers in their self-assessments and response time to the hazards in the video clips. Although many studies attempted to reveal the relationship between young novice drivers’ response time to the hazards and their accident involvements [2, 8], the relationship between their self-assessments and the number of traffic violations in the driving of past year has not been largely explored. The main purpose of the present study was to explore the characteristics of subjectively and objectively measured hazard perception ability of violation-free and violation-involved young drivers. The second purpose was to examine the relationship between young drivers’ self-assessment and their response time to the hazards and the number of traffic violations.

2 Methods 2.1

Participants

Forty-seven young novice drivers were recruited through traffic channel of Dalian radio station. Participants were divided into two driver groups according to the number of traffic violations in the driving of past year. Violation-free group included 35 drivers (20 males), age ranged from 19 to 25 years (M = 23.60, SD = 2.44), with less than 2 years’ driving experience (M = 0.94, SD = 0.33). Violation-involved group included 12 drivers (7 males), age ranged from 20 to 25 years (M = 23.67, SD = 2.50), with less than 2 years’ driving experience (M = 1.06, SD = 0.39). All participants’ visual version was normal or corrected-to-normal. Participants did not attend to any hazard perception test prior to this experiment. The two driver groups were not significantly different in their gender ratio, age and driving experience.

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2.2 2.2.1

33

Materials and Procedure Hazard Perception Questionnaire

A six item-hazard perception questionnaire was used to assess young novice drivers’ self-assessed hazard perception ability [9]. Participants were asked to rate how skilful they are at the six items by comparing to their peers. The items were rated from 1 (much worse) to 7 (much better) with a mid-point of 4 (the same). The reliability of the questionnaire was 0.91. 2.2.2

Hazard Perception Task

A hazard perception task, included 18 dynamic traffic video clips, was used [10]. All video clips were filmed from the drivers’ perspective around Dalian urban areas under fine weather. Each clip showed a situation where a potentially hazardous event was developing slowly when the camera-car was approaching. The length of each clip ranged from 9 to 21 s. The visibility of the hazards was continuous and the visible time of each hazard ranged from 3 to 6 s. The task showed good discriminate validity in a previous study [11].

2.3

Experimental Design and Procedure

A one-factor experiment design was employed. The between-groups factor was driver group (violation-free driver vs. violation-involved driver). The dependent variables were response time, score of self-assessed hazard perception ability. Response time was calculated as the time from the hazard onset to the moment that a response was made. Self-assessment score was obtained by averaging the score of the six items on the questionnaire. Participants first signed an informed content and then took two practice clips. Participants were asked to click to left mouse button quickly when they detected a hazard. Custom software was used to record participants’ response time. Finally, 16 video clips were randomly assigned to each participant on a 17-inch monitor at a resolution of 1280  720 pixel.

3 Results 3.1

Response Time

Independent t sample test was used to compare the mean response time in the two driver groups. Results showed that violation-free drivers (M = 1.91, SD = 0.34) responded to the hazards faster than violation-involved drivers (M = 2.20, SD = 0.35), t(45) = − 2.31, p < 0.05, Cohen’d = − 0.84.

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Table 1 Partial correlation matrix

3.2

Response time Traffic violations 0.22 Response time Note *p < 0.05, **p < 0.01

Self-assessment score 0.42** 0.02

Self-assessment Score

Independent t sample test was used to examine the difference in self-assessment score. Results showed that violation-involved drivers (M = 4.98, SD = 0.86) have higher self-assessment score than violation-free drivers (M = 4.22, SD = 0.83), t(45) = 2.45, p < 0.05, Cohen’d = 0.899. Violation-involved drivers’ self-assessment score was also higher than the average score of the whole sample (M = 4.38, SD = 0.88).

3.3

Correlation Analysis

Partial correlation analysis was conducted to examine the relationship between the number of traffic violations, self-assessment and response time after controlling gender, age, driving experience and weekly driving mileage, and the results are shown in Table 1. Table 1 shows drivers’ self-assessments correlated positively with their number of traffic violations from the last year. Notably, drivers’ response time correlated positively with their self-assessments and the number of traffic violations, though the coefficients were not significant.

4 Discussions The present study examined the consistency of subjectively and objectively measured hazard perception ability of young Chinese drivers using a video-based hazard perception test and a self-reported hazard perception questionnaire. This study found no significant correlations between drivers’ self-assessments and their response time to the hazards. The findings suggested that some drivers in this study might estimate their hazard perception ability inaccurately or they suffer from experience-related deficit in detecting and responding to the hazards or the two reasons both contribute to this phenomenon. The results were inconsistent with one previous study showing that young male drivers’ self-assessments correlated significantly with their response time to the overt hazards in a driving simulator [4]. Although the hazards in the present study were all visible ones, future studies should focus on the influencing of hazard types [12]. Another possible explanation

Subjectively and Objectively Measured Hazard Perception …

35

was that the hazards in the video clips did not correspond to the items in the questionnaire. Furthermore, the present study found violation-involved drivers responded to the hazards slower than violation-free drivers. Violation-involved drivers also have higher self-assessments than violation-free drivers. Given violation-involved driver’ self-assessments were higher than the mean score of the whole sample, it is reasonable to conclude that young drivers who have traffic violations in the driving of past year are at higher risk, probably due to their overestimation of hazard perception ability. Previous study has showed that young drivers who overestimated their hazard perception ability have a higher risk threshold and they might not respond to a potential hazard until the risk level of the hazard was unacceptable for them [13, 14]. The present study was the first to examine the relationship between young drivers’ self-assessments and the number of their traffic violations. Results showed that young drivers who rated their hazard perception ability higher tended to have more traffic violations. This was consistent with previous studies showing that drivers with higher self-assessments are more prone to traffic accidents [5, 15]. Due to traffic accidents were rare in driving and the small sample of participants, the present study did not investigate the relationship between self-assessments and response time of accident-free and accident-involved young drivers. Future studies were needed to solve this to provide more information for the development of training inventions for young Chinese drivers. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Liaoning Normal University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Wetton MA, Horswill MS, Hatherly C et al (2010) The development and validation of two complementary measures of drivers’ hazard perception ability. Accid Anal Prev 42(4):1232– 1239 2. Horswill MS, Hill A, Wetton M (2015) Can a video-based hazard perception test used for driver licensing predict crash involvement? Accid Anal Prev 82:213–219 3. Pelz DC, Krupat E (1974) Caution profile and driving record of undergraduate males. Accid Anal Prev 6(1):45–58 4. Ābele L, Haustein S, Møller M et al (2018) Consistency between subjectively and objectively measured hazard perception skills among young male drivers. Accid Anal Prev 118:214–220 5. Horswill MS, Waylen AE, Tofield MI (2004) Drivers’ ratings of different components of their own driving skill: a greater illusion of superiority for skills that relate to accident involvement. J Appl Soc Psychol 34(1):177–195 6. Martinussen LM, Møller M, Prato CG (2017) Accuracy of young male drivers’ self-assessments of driving skill. Transp Res Part F Traffic Psychol Behav 46:228–235

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7. Sümer N, Ünal AB, Birdal A et al (2007) Comparison of self-reported and computer-based hazard perception skills among novice and experienced drivers. In: Proceedings of the fourth international driving symposium on human factors in driver assessment, training and vehicle design 8. Cheng AS, Ng TC, Lee HC (2011) A comparison of the hazard perception ability of accident-involved and accident-free motorcycle riders. Accid Anal Prev 43(4):1464–1471 9. White MJ, Cunningham LC, Titchener K (2011) Young drivers’ optimism bias for accident risk and driving skill: accountability and insight experience manipulations. Accid Anal Prev 43(4):1309–1315 10. Sun L, Li S, Chang R (2019) Development and validity of Chinese hazard perception test. Lect Notes Electr Eng 527:257–262 11. Sun L, Dou G (2019) Computer-based hazard perception study in Chinese environmental effects of driving experience and age. Ekoloji 28(107):4311–4317 12. Sun L, Chang R, Li S (2018) Effects of driving experience and hazard type on young drivers’ hazard perception. Lect Notes Electr Eng 456:11–16 13. Deery HA (1999) Hazard and risk perception among young novice drivers. J Saf Res 30 (4):225–236 14. Ventsislavova P, Gugliotta A, Peña-Suarez E et al (2016) What happens when drivers face hazards on the road? Accid Anal Prev 91:43–54 15. Ma Y, Sun L (2018) Reliability and validity of self-assessment of driving skills scale in Chinese drivers. Adv Psychol 8(6):848–854

Experimental Research on Layout Accessibility of Individual Load-Carrying Equipment Yaping Wang and Shanlin ChenCai

Abstract Using three-dimensional motion capture and surface myoelectricity system, this study showed the characteristics of upper limb’s movement and surface electromyography in the process of picking and placing the Soldier System’s module on load-carrying equipment. The study aims to evaluate the accessibility to nine representative layout locations of load-carrying equipment. It can make an important contribution to the layout and optimization of individual load-carrying equipment. The results of this investigation showed that: (1) The maximum change of the upper arm’s angular velocity and integrated electromyography of muscles biceps brachii both can evaluate accessibility, yet the former had more significant and representative than the latter. (2) There was a significant positive correlation between the accessibility of soldier’s carriers in front part of the body and the movement distance of hand. Soldier System’s modules which are high frequently accessed were appropriate for the more accessible position. Keywords Load-carrying equipment Surface electromyography


Layout
Accessibility
Motion capture


1 Introduction Soldier System is the modern military personal equipment which combined multiple high technologies. It is to integrate the soldier with technologies, thereby enhancing lethality, survivability, sustainment, mobility and awareness [1]. Individual soldier needs to carry over ten modules, including cartridge holders, soldier computers, stations, and GPS. Individual load-carrying equipment is designed to accommodate Soldier System’s modules, such as cartridge magazines, gas masks, flares, and grenades. The issue of layout accessibility of new individual Y. Wang (&)
S. ChenCai School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_5

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load-carrying equipment has received considerable critical attention. The study aims to evaluate accessibility to nine representative layout locations of individual load-carrying equipment. It can make an important contribution to the layout and optimization of individual load-carrying equipment, thus relieving soldiers’ fatigue and increasing combat efficiency. There are relatively few historical studies in the area of individual load-carrying equipment’s accessibility. Harman et al. [3] conducted the experiment to compare the prototype load-carrying systems’ effects on soldiers’ physiological, biomechanical, and maximal performance responses when carrying light, medium, and heavy loads. The subjects’ parameters of body movement angles and velocity were obtained by optical motion capture instrument. Using the motion capture measurement, Woods et al. [6] analyzed movement condition of 12 subjects when they were wearing US army ALICE load-carrying equipment system. Chen [1] evaluates accessibility of individual load-carrying equipment using 3D simulation system. Dong [2] divides human body surface into 32 parts according to actual situation of Chinese army individual load-carrying equipment layout. These findings enhance our understanding of individual load-carrying equipment’s accessibility. However, there are three major limitations of these researches: (1) The researches are mainly concerned with simulation method and subjective survey. Limited by the lack of measurement means, less objective experimental data is obtained only by motion capture measurement. (2) There are only three accessibility grades for each area: comfortable accessibility, ultimate accessibility, and inaccessibility. (3) No objective indicator is extracted for evaluating accessibility grades. By comprehensive measurements of three-dimensional motion capture and surface myoelectricity, this paper seeks to examine the changing nature of upper limb’s movement and surface electromyography (sEMG) in the process of picking and placing Soldier System’s module in different areas on individual load-carrying equipment. The objective quantification evaluation of individual load-carrying equipment was proposed.

2 Materials and Methods The characteristics of upper limb’s movement were obtained using Codamotion 3D motion capture system to capture characteristic points on the subjects’ body. The layout of markers is shown in Fig. 1. Then, using TB0820 surface myoelectricity system, the characteristics of sEMG were obtained through electrode slices on brachioradialis, musculus biceps brachii, and middle deltoid of right upper limb. The electrode slices were affixed to the skin using double-sided tapes, as shown in Fig. 2. According to the actual situation, nine operating positions (hereinafter referred to as position) were designed on individual load-carrying equipment. There were seven positions in the front (including the column near manipulator, the column

Experimental Research on Layout Accessibility of Individual …

Fig. 1 Layout of characteristic point

Fig. 2 Positions of electrode slice

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Fig. 3 Schematic diagram of operating positions

away manipulator, and the middle row) and two positions in the back. Specific layout and serial numbers are shown in Fig. 3. Light carriage bags were sewed in each position with a 1 kg standard wedge. The test procedure was as follows: The subject was in standing position with arms drooping naturally. When the command “start” was heard, the subject took the standard wedge from light carriage bag with right hand. Next, the subject held the standard wedge for three seconds in front of chest. Then, the subject put the standard wedge back into light carriage bag. Finally, the subject returned initial position with arms drooping naturally. Each experiment repeated five times with an interval of 1 min for eliminating errors and avoiding fatigue. There was a 5-min break after finishing one position experiment. The subject repeated the experiment until all nine positions were completed. There were 5 subjects aged 24–28 years in good physical and mental condition, without dyskinesia or injured limbs. The subjects had not performed strenuous physical activity three days prior to the experiment. Data management and analysis were performed using SPSS. A difference with p < 0.05 was considered statistically significant.

3 Results 3.1

Kinematic Characteristics of the Upper Arm

The upper arm is responsible for picking and placing the wedge. Point E and Point D (as shown in Fig. 1) were joined as the upper arm. The motion characteristics were decomposed in the sagittal and coronal planes.

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Fig. 4 Upper arm’s rotational angle on Position 1

For different positions, there was a similar change rule of the upper arm’s angle. Taking that on Position 1 as an example, the upper arm’s angle is shown in Fig. 4. It illustrated that the change rule of the upper arm’s angle in sagittal plane was similar to that in coronal plane. There were five stages as follows: (1) Stage 1, moving hand from the initial position to the operating position; (2) Stage 2, holding the wedge from the operating position to the chest; (3) Stage 3, keeping the wedge in front of the chest for 3 s; (4) Stage 4, putting the wedge back to the operating position; and (5) Stage 5, moving hand from the operating position to the initial position. There was obvious symmetry of angle. It illustrated that the upper limb’s paths on picking the wedge were approximately similar to that on putting the wedge back after human body automatically optimized the path. Figure 5 shows that the rule of the upper arm’s angular velocity in sagittal plane was similar to the rule of angle. The process was also divided into five stages. There were two peak angular velocities in the two moments, when the arm was raised to the operating position and the wedge was put in front of the chest. The curve of the upper arm’s angular velocity also was approximately symmetrical.

Fig. 5 Upper arm’s angular velocity in sagittal plane on Position 1

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Characteristic on Different Operating Positions

The upper arm’s angles at the end of Stage 1 on all positions are shown in Fig. 6. The angle was relative value compared with that in initial position. On Positions 1, 3, and 6 which were in the column near manipulator, the angles in sagittal plane and coronal plane were both positive. There had been a gradual decrease from Position 1 to 6. On Positions 2, 5, and 7 which were in the column away manipulator, the angles in sagittal plane and coronal plane were negative. There had been a gradual decrease from Position 2 to 7. On Positions 3, 4, and 5 which were in the middle row, the angles in sagittal plane and coronal plane changed from positive to negative. The maximum changes of the upper arm’s angular velocity in sagittal plane on all positions are shown in Fig. 7. The graph showed that there had been a steady decrease in the vertical positions, whereas there had been a steady increase in the horizontal positions. It indicated that there was a significant positive correlation between the distance from initial position and the maximum change of angular velocity. In terms of numerical value, the maximum changes of angular velocities on Positions 1 and 3 were 48 and 39% higher than that on Position 6, respectively.

Fig. 6 Upper arm’s maximum angle corresponding to Position No

Fig. 7 Maximum change of angular velocity corresponding to Position No

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The maximum changes of angular velocities on Positions 2 and 5 were 51 and 12% higher than that on Position 7, respectively. The maximum changes of angular velocities on Positions 5 and 4 were 25 and 18% higher than Position 3, respectively. The maximum change of angular velocity was more regular than the angle at the end of Stage 1. The representation value based on the maximum change of angular velocity was superior to that based on the angle.

3.3

Feature of SEMG

SEMG signal is a bioelectricity signal that is conducted and recorded by surface electrodes from skin surface as skeletal muscles work. SEMG is related with muscle activity and functional status. Therefore, it can reflect activity of nerve-muscle to a certain degree [5]. In general, sEMG signal obtained directly by surface myoelectricity instrument is one-dimensional time series signal. It is the superposition of the electric potential generated by muscle motor units in time and space. In general, sEMG signals are analyzed in time domain and frequency domain. Integrated electromyogram (iEMG) refers to the total discharge of muscle motor units within a certain period of time [4], which usually used to reflect activity level of muscles. IEMG was adopted in this study. Based on statistical analysis, the findings of the study indicated that musculus biceps brachii was a major contributor to the process of picking and placing the wedge. In Fig. 8, there was a clear trend of decreasing of iEMG of three subjects’ musculus biceps brachii on Positions 1, 3, and 6. There was a similar trend on Positions 2, 5, and 7, while on Positions 3, 4, and 5(horizontal direction), there was no significant difference. The iEMGs on Positions 1 and 3 were higher about 58 and 18% than that on Position 6, respectively, while the iEMGs on Positions 2 and 5 were higher about 11 and 5% than that on Position 7, respectively. Although the change rule was similar to the maximum change of angular velocity, there was a certain difference in numerical value. A possible explanation for this might be that the iEMG was a consequence of musculus biceps brachii working only. However, the maximum change of angular velocity was a consequence of many multiple muscles working together.

Fig. 8 iEMG of musculus biceps brachii on all positions

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Fig. 9 iEMG of the muscle generating maximum force on all positions

On Positions 8 and 9, iEMGs of three muscles all were high. The muscle generating maximum force is deltoid. The iEMG of deltoid was higher than that of musculus biceps brachii in the above seven positions (as shown in Fig. 9). It showed that the higher level of muscle activity was required when picking and placing the wedge on Positions 8 and 9. Therefore, muscles were especially prone to fatigue. It was poor accessibility on Positions 8 and 9 which were not suitable for placing equipment that need to be picked frequently.

4 Discussion Table 1 shows the average linear distances between the initial position and the operating position. Through the Pearson correlation analysis between the linear distance and the maximum change of angular velocity/iEMG, the line distance had strong positive correlation with the maximum change of angular velocity and iEMG. As shown in Table 2, the correlation coefficient with the maximum change of angular velocity was greater than that with iEMG. There was a strong correlation between the accessibility of load-carrying equipment and the movement distance of hand. The longer movement distance, the more muscles work; thus, muscles were more prone to fatigue. Therefore, the accessibility in this area was relatively poor. Meanwhile, it indicated that the upper arm’s maximum change of angular velocity was more significant and representative as the evaluation indicator of muscle work level or accessibility. Table 1 Distance between the initial position and the operating position Position No Distance Unit: cm

1

2

3

4

5

6

7

50.2

58.3

35.0

38.1

46.1

20.3

36.1

Table 2 Correlation coefficient r Distance

The maximum change of angular velocity

iEMG

0.78

0.64

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5 Conclusions Using three-dimensional motion capture system and surface myoelectricity measurements, this study had shown characteristics of the upper arm’s movement and surface electromyography in the process of picking and placing the wedge. This study had shown that: (1) Accessibility of individual load-carrying equipment in front part of the body had positive correlation with the movement distance of hand. (2) The maximum change of the upper arm’s angular velocity and iEMG of musculus biceps brachii both can evaluate accessibility, yet the former had more significant and representative than the latter. (3) Accessibility was bad on the back of individual load-carrying equipment. Soldier System’s modules which do not picked very frequently should be placed in the back. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Nanjing University of Science and Technology. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Chen X, Dong D, Zu Y et al (2009) Preliminary study on the ergonomics imitation and evaluation technique for the single soldier equipment system. China Pers Protective Equip 2:12–15 2. Dong D, Wang L, Yuan X et al (2010) Experimental research on the determination of human body surface reachable grade. Acta Armamentarii 31(7):1003–1008 3. Harman E, Frykman P, Pandorf C et al (1999) Physiological, biomechanical, and maximal performance comparisons of soldiers carrying loads using U.S. Marine Corps Modular Lightweight Load-Carrying Equipment (MOLLE), and U.S. Army Modular Load System (MLS) protypes 4. Pope GD (1998) Introduction to surface electromyography. Physiotherapy 84(8):405 5. Wang J, Jin X (2000) sEMG signal analysis method and its application research. China Sport Sci Technol 36(8):26–28 6. Woods RJ, Polcyn AF, O’Hearn BE et al (1997) Analysis of the effects of body armor and load-carrying equipment on soldiers’ movements. Part 1. Technique Comparisons

Evaluation and Strategy Analysis of Students’ Mental Health in Semi-military Schools Min Wang, Jintao Yu and Peng Wang

Abstract In order to evaluate the mental health condition of students in semi-military schools, this paper establishes a comprehensive evaluation system based on SCL-90 measurement and seven more affecting factors at first, then the relationship between total score, single factor and affecting factor is analyzed. On the basis of the main factors affecting mental health, some targeted strategies are proposed for students with mental health problems in semi-military schools. For the purpose of testing the effectiveness of each strategy, a quantile regression model is constructed to measure the utility value of different strategy and execute the quantitative analysis. Finally, the result shows that the strategies are effective for semi-military school students to varying degrees.







Keywords Mental health evaluation Correlation analysis Multivariate regression analysis Quantile regression Semi-military school







1 Introduction With the fast development of the society, mental health problems have been paid more and more attention. In semi-military schools, improving the psychological quality of the young students is a significant part of the school’s talent development and teaching management [1]. In order to detect the mental health problems in advance and prevent them before happening, it is necessary to evaluate and analyze the psychological status of students scientifically. The Symptom Checklist-90 (SCL-90) is a relatively brief self-report psychometric instrument designed to evaluate a broad range of psychological problems and symptoms of psychopathology [2]. Based on SCL-90, scholars have done a lot of research on evaluating people’s mental health condition and related strategy analysis [3–5]. In this paper, an index system of factors affecting students’ mental health is established M. Wang (&)
J. Yu
P. Wang Army Academy of Artillery and Air Defense, Hefei 230031, Anhui, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_6

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and some primary ones are extracted, then the influence on students is analyzed on the basis of SCL-90. Furthermore, the strategies are proposed and their effectiveness is corroborated.

2 Quantitative Analysis of Affecting Factors of Students’ Mental Health Based on SCL-90 Measurement The SCL-90 measurement involves ten symptom factors which are somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depressive symptoms, anxiety symptoms, hostile emotions, fear symptoms, paranoid modality, psychotic status and others. The questionnaire contains ninety items that are scored according to five levels which can roughly evaluate the students’ mental health. The score of the first nine factors excepting others are denoted as B1*B9 successively. Apart from the above ten symptom factors, the factors affecting the mental health include seven other aspects which are family structure, upbringing, environmental adaptability, administrative management, attitude of a leader, interpersonal communication and self-evaluation of health. For convenience, we denote the affecting factors as F1*F7, respectively. In the following, we take total score and factor score of SCL-90 as dependent variables and seven affecting factors as independent variables for multivariate regression analysis. Therefore, the evaluation index system is composed of the total score of SCL-90, symptom factors and affecting factors.

2.1

Evaluation Index Quantification

Let aj be the score of each item, where 1  j  90 and j 2 N, then the total score A can be calculated as below [4]: A¼

X

aj ; 1  j  90; j 2 N

ð1Þ

According to the description of the classification level, the affecting factors can be converted into the following scoring standards [3]. F1: F2: F3: F4: F5: F6: F7:

parents = 1, single parent = 2, other = 3; mandatory = 1, indulgent = 2, spoiled = 3, democratic = 4; adaptive = 1, less adaptive = 2, not adaptive = 3; democratic = 1, little mandatory = 2, mandatory = 3; very concerned = 1, concerned = 2, less concerned = 3, not concerned = 4; 5 + friends = 1, 3*5 friends = 2, 1*2 friends = 3, no friends = 4; very good = 1, good = 2, average = 3, bad = 4, very bad = 5.

Evaluation and Strategy Analysis of Students’ Mental …

2.2 2.2.1

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Quantitative Analysis of Affecting Factors Correlation Analysis of Affecting Factors

In order to analyze the degree of correlation of affecting factors, 1214 students were randomly selected from three semi-military schools for SCL-90 mental health testing. On the basis of the data, correlation analysis and multivariate item-by-item linear regression are executed by means of SPSS. The correlation coefficients of the affecting factors are shown in Table 1. From the results of Table 1, we can draw a conclusion that the major affecting factors of mental health are upbringing, administrative management, family structure and self-evaluation of health. What’s more, family structure is significantly positively correlated with self-evaluation of health, while upbringing is significantly negatively correlated with administrative management.

2.2.2

Multiple Regression Analysis of Total Score and Single Symptom Factor

When doing multiple regression analysis, 100 samples were randomly extracted from the database and SPSS was also used for regression analysis. The regression results are shown in the following Table 2. According to the data processing results, the multivariate regression equations of the total score and single symptom factor can be established, respectively. Furthermore, the range 0.207–0.521 of ΔR2 indicates that the 20.7–52.1% variation of single symptom factor score is determined by the affecting factors, which indicates that the mental health test results are related to seven affecting factors, and attitude of a leader, interpersonal communication and self-evaluation of health are the main affecting factors. Those results are basically consistent with the empirical analysis.

Table 1 Means, standard deviations and correlation coefficients of the affecting factors Mean

Standard deviation

F1

F2

F3

F4

F5

F6

F7

F1 1.22 0.625 1.000 0.066 0.233 0.000 0.198 0.063 0.381* F2 2.73 1.273 0.066 1.000 −0.145 −0.529 0.205 −0.304 −0.039 0.566 0.233 −0.145 1.000 0.129 0.176 0.016 0.296 F3 1.53 0.787 0.000 −0.529 0.129 1.000 0.078 0.253 0.125 F4 2.01 0.821 0.198 0.205 0.176 0.078 1.000 0.084 −0.265 F5 1.95 0.769 0.063 −0.304 0.016 0.253 0.084 1.000 0.296 F6 1.48 0.832 0.381* −0.039 0.296 0.125 −0.265 0.296 1.000 F7 1.88 Note *represents a significant correlation with 0.05 level (both sides); ‘Bold emphasis’ represents a significant correlation with 0.01 level (both sides)

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Table 2 Results of multiple regressions A B1 B2 B3 B4 B5 B6 B7 B8 B9

R2 0.565 0.381 0.526 0.545 0.612 0.584 0.353 0.507 0.536 0.551

ΔR2 0.465 0.253 0.415 0.449 0.521 0.490 0.207 0.391 0.426 0.458

Constant 51.290 0.366 0.954 0.744 0.633 0.260 0.821 0.579 0.153 0.657

F1 −11.038 −0.212 −0.112 −0.098 −0.141 −0.076 0.044 −0.189 0.012 −0.181

F2 −4.710 −0.023 −0.108 −0.107 −0.075 −0.038 −0.093 −0.037 0.025 −0.029

F3 −0.826 0.179 −0.139 −0.090 −0.074 0.010 0.016 0.043 0.017 −0.063

F4 1.310 0.058 −0.018 −0.014 −0.012 0.041 −0.027 −0.061 0.098 0.042

F5 19.287 0.201 0.345 0.231 0.236 0.209 0.185 0.231 0.125 0.157

F6 26.174 0.190 0.245 0.358 0.315 0.383 0.192 0.386 0.381 0.256

F7 15.782 0.218 0.194 0.182 0.218 0.221 0.081 0.092 0.067 0.193

3 Psychological Counseling Strategies and Their Verification 3.1

Psychological Counseling Strategies

From the above evaluation system, the semi-military school can concentrate on attitude of a leader, interpersonal communication and self-evaluation of health when providing psychological counseling. Combining with the daily life and paying attention to the significant positive correlation between family structure and self-evaluation of health, also the significant negative correlation between upbringing and administrative management, some suggestive psychological counseling strategies are given as follows: 1. Paying attention to ideological guidance and enriching students’ horizons. 2. Creating a harmonious atmosphere and cultivating students’ environmental adaptability. 3. Innovating the management mode and clarifying the significance of management. 4. Focusing on the family situation and alleviating the burden of thought.

3.2

Strategy Verification Based on Quantile Regression Analysis

In 1978, Koenker and Bassett proposed the idea of quantile regression [6], which compensated for the deficiency of traditional least squares in regression analysis. Definition 1 Let the probability distribution function of the random variable Y be F(y) = P(Y  y), then the quantile function of variable Y is defined as follows:

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QðsÞ ¼ inf fy : FðyÞ  sg ð2Þ Suppose Y0, Y1,…, Yn is a random sample of random variable Y, then the mean of the sample is the optimal solution of the following expression: min

n X

ðyi  bÞ2

ð3Þ

i¼1

and the quantile function QðsÞ is the optimal solution of the following expression: " min b

X

sjyi  bj þ

yi  b

X

# ð1  sÞjyi  bj

ð4Þ

yi  b

Definition 2 For all 0\s\1, the loss function is an expression as follows:  qs ðuÞ ¼

su ðs  1Þu

u0 u\0

ð5Þ

For the quantile regression model, the linear programming method (LP) can be used to estimate the minimum weighted absolute deviation, so as to obtain the regression coefficients of the explanatory variables.

3.2.1

Quantitative Prediction Analysis Model of Strategies Based on Quantile Regression

Assume that x1, x2, x3 and x4 represent the utility value of the four strategies, respectively, which reveal whether the strategy is applicable to the object of psychological counseling and are related to the internal causes and external manifestations of psychological problems. We can also provide more effective strategies according to the utility values. Next, the quantile regression method is introduced into the quantitative prediction of the effectiveness of the strategies and the linear model of the effectiveness is constructed as follows: yi ¼ xi bs þ uis

ð6Þ

Qs ðyi jxi Þ ¼ xi bs

ð7Þ

then, one can get:

where yi represents the effectiveness of strategy i, uis represents the error, bs is s regression quantile, a parameter to be estimated, and s is the quantile probability taken any value between 0 and 1. In practice, the effectiveness of strategy cannot be precisely defined, therefore, the value of yi can be simplified as:

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 yi ¼

1 0

yi  0 yi \0

improved not improved

ð8Þ

If the condition of a student with psychological problems is improved, then yi = 1, and the probability of this situation can be calculated under the conditional quantile model as follows: Z1 pi ¼ pðyi¼1 jxi Þ ¼ pðuis   xi bs Þ ¼

Iðxi bs  0Þds

ð9Þ

0

where I(x) represents the indicative function. The Eq. (9) shows that pi is a function of xi and bs , and bs can be obtained from the following formula: bðsÞ ¼ arg min

n X

b

i¼1

qs ðyi  xi bÞ

ð10Þ

If s ranged from 0.1 to 0.9 indicates evaluating the effectiveness of predict strategy from nine different levels, then the Eq. (9) can be simplified as: Z1 pi ¼

I ðxi bs  0Þds ¼ 0

0:9 1X I ðxi bs =kbs k  0Þ 9 s¼0:1

ð11Þ

where kbs k represents the Euclidean distance norm of bs . 3.2.2

Analysis of the Effectiveness of Strategies

Quantile regression refers to the marginal effect of explanatory variables (four strategies) on the explained variable (mental health improvement) with a particular quantile, thus providing more valuable conclusions for predictive analysis of strategic effectiveness. If we take the quantile from 0.1 to 0.9 arithmetically on nine different levels, then the relation between the utility value of strategy xi and the quantile bs can be calculated on the basis of 1214 sample data. By means of Eviews, the final result is shown in Table 3. To be more intuitive, Table 3 is plotted in MATLAB as shown in Fig. 1. It can be concluded that all strategies have improved mental health condition to a certain extent with the increase of probability of mental health improvement. What’s more, strategy 2 and 3 have improved mental health condition more effectively, while the effectiveness of strategy 1 and 4 are relatively mild. Combining the correlation analysis of seven affecting factors with the quantile regression analysis of strategy effectiveness, one can draw the conclusion that mental health is the result of interaction between individuals and the environment,

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Table 3 Estimation of xi value by quantile regression x1 x2 x3 x4

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

8.43 4.79 7.52 11.5

8.51 7.39 10.27 10.75

8.66 8.89 13.01 11.17

8.75 9.76 15.46 11.53

9.41 12.36 17.17 12.96

10.18 13.68 18.31 14.57

11.10 16.52 21.49 16.43

13.12 27.27 25.63 18.58

15.69 31.96 28.62 23.03

0.6

0.7

35

x

30

x 25

x x

20

1 2 3 4

15 10 5 0 0.1

0.2

0.3

0.4

0.5

0.8

0.9

Fig. 1 Effectiveness of strategies

mainly including natural environments, social factors and individual adaptation to the environment. A good external environment can create a harmonious and healthy psychological atmosphere, which has a subtle influence on the cultivation of good psychological quality, and a predominant psychological atmosphere will also provide opportunities for the healthy development of students. Therefore, the semi-military school is supposed to build up a brilliant interpersonal atmosphere and living and working conditions, strengthen the psychological counseling regularly, carry out education on fostering morally sound values and outlook on the world and life and promote the development of students’ physical and mental health.

4 Conclusion The paper establishes a comprehensive evaluation system to evaluate the mental health status of students in semi-military schools. Through correlation analysis and multiple regression, the main factors affecting students’ mental health are analyzed.

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On the basis of these factors, some targeted suggestions are proposed for students with mental health problems in semi-military schools. The effectiveness of the proposed strategies is tested through the quantitative prediction analysis model of strategies based on quantile regression. In general, using the models to judge the individual’s psychological status is basically consistent with the actual condition. It can test the suffered students’ current status scientifically and effectively in semi-military schools, so it is more suitable for students’ mental health evaluation and strategy analysis.

References 1. Zhang D (2002) Strengthen mental health education in schools and foster students’ psychological quality. J Hebei Normal Univ Educ Sci Edn 1:17–23 2. Pearson (2016) Clinical psychology. Pearson Education, New York 3. Huang Y, Li L (2009) SCL-90 as measurement of mental health in college students: a meta-analysis. Chin Mental Health J 23:366–371 4. Tang Q, Cheng Z (1999) The use and reanalysis of SCL-90 in China. Chin J Clin Psychol 1:16–20 5. Tong H (2010) A research of twenty years’ vicissitude: SCL-90 and its norm. Psychol Sci 33:928–930 6. Koenker R, Bassett G (1978) Regression quantiles. Econometrica 46:33–50

Study on Classification and Characteristic of Type of Lower Part of Body of Female College Students Jiandie Lin, Yuxiu Yan, Zimin Jin and Lu Lin

Abstract The accurate judgment and classification of the lower part of body of female is crucial for the fit and the comfort of female trousers. This paper took the type of lower part of the body of female college students as the main research object, collected the body data of the female by the non-contact three-dimensional human body scanner, and analyzed the data to obtain the three main components, and types of the waist–abdomen–buttock of female college students were divided into eight categories. The relationship between the circumference direction variables and the height and body mass index and the relationship between the length direction variable and the hip or height were obtained by regression analysis. Based on these, the rules of data generation of the lower part of female college students were obtained, and it was verified that the calculation results of the rules were effective within an error of 1 cm, which provided data basis of human body for the rapid design of the fit comfort pants version.




Keywords Type of lower part of body Factor analysis type Cluster analysis Regression relationship








Classification of body

1 Introduction With the change of the living environment and the dietary structure, the problem that the standard of garment size cannot match human body is becoming more and more serious. In order to satisfy the increasing requirements of consumers for the fit and comfort clothing, it is necessary to study the relationship between various parts of the human body and the structure of the garment one by one [1]. As the development of science and technology, the classification and the discrimination of human body type has become a research hot spot in the field of body measurement and the garment [2–4]. Many scholars mainly focus on the study of the J. Lin
Y. Yan (&)
Z. Jin
L. Lin Zhejiang Sci-Tech University, Hangzhou, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_7

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classification and discrimination of the type of the whole body or the upper body [5–8]. The classification and discrimination of the type of lower body are particularly important for making the fit and comfort trousers version; in addition, the psychological needs of the personalized apparel and the digital trend of the clothing prompt that the clothing production rely on the information technology. In the paper, factor analysis, cluster analysis, regression analysis, and other data analysis methods were used to study the classification and discrimination of types of lower body of female college students, and the rules table for generating body shape data was obtained, which provided the basis of human body data for the rapid design of the fit and comfortable pants.

2 Data Acquisition and Preprocessing In the paper, 76 female body size data were collected by the [TC]2 dimensional body measurement system. The measured objects were 18- to 25-year-old female college students with the height of 147.0–170.0 cm and the body weight of 37.0– 69.0 kg. In order to avoid natural light interference the measurement results, a dark room with the ambient temperature of (26 ± 2) °C and the relative humidity of (60 ± 5)% was ready for the nude measurements, and the room was suitable. During the measurement, participants should be uniform dressing and maintain a uniform posture at the specified measurement position to ensure the accuracy of the measurement data. Referring to the GB/T 1335-2009, types of the lower part of the body were divided by the height and the range difference of waist girth and hip girth. In order to meet the research purpose, the paper selected the main measurement locations, including the length direction variables and the circumference direction variables, a total of 32 items, which reflected the basic body type of the lower body and were the key measurement sites for trousers. By data inspection, missing value analysis, normality test, and correlation test on the collected data, some abnormal values were eliminated, and 72 real and effective sample data were finally retained.

3 Types Analysis of the Lower of the Body 3.1

Factor Analysis

The functional distribution on the lower part of the body surface includes fitting area, function area, free area, and design area [9], as shown in Fig. 1. According to the functional distribution, the parts related to the design of the clothing model are mainly distributed on waist, buttocks, and abdomen that support the lower part of

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Fig. 1 Functional distribution on body surface

the body, and that are also the main area that determines the fit of the pants. Therefore, this paper is focused on researching the shape of the waist–abdomen– buttock of female college students from making pattern of trousers. From the distribution of female lower part of the body surface, waist girth, front waist girth, back waist girth (Wb), waist width, abdominal girth, front abdominal girth, back abdominal girth, abdominal width, hip girth, front hip girth, back hip girth (Hb), hip width, hip–waist difference (HWD), waist-to-hip ratio (WHR), and waist–abdomen difference(WAD) were analyzed by factor analysis, and a few influence factors are summarized from 15 measurement indicators. In factor analysis, the number of factors, which is greater than 1, is usually used as the eigenvalue, as shown in Fig. 2, the three components had a variance cumulative rate of 93.274%. It could be considered that these three factors contain most of the information of all variables. The maximum variance method was used to perform orthogonal rotation on the factor load matrix to describe the information contained in the common factor. Table 1 showed the component score matrix after orthogonal rotation. Among the component factor scores, the absolute value of the component greater than 0.9 was chosen as the index factor for its coverage. Therefore, the first principal component factor in Table 1 includes factors: hip girth, front hip girth, back hip girth, and hip width. The variance contribution rate is 45.2221%, and it is the factor describing the characteristics of the hip part of female. The second principal component is WHR, and the variance contribution rate is 28.7923%. The third principal component is WAD, and the variance contribution rate is 19.2523%.

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Fig. 2 Scree plot

Table 1 Component score coefficient matrix after orthogonal rotation Standardized measurement index variables

Components 1

2

3

Waist girth Front waist girth Back waist girth Waist width Abdominal girth Front abdominal girth Back abdominal girth Abdominal width Hip girth Front hip girth Back hip girth Hip width HWD WHR WAD

0.719 0.726 0.704 0.569 0.559 0.730 0.326 0.481 0.980 0.955 0.964 0.937 0.175 0.097 −0.131

0.676 0.661 0.686 0.630 0.352 0.035 0.441 0.355 0.084 0.127 0.038 0.137 −0.976 0.986 −0.379

0.144 0.143 0.145 0.203 0.744 0.399 0.738 0.775 0.156 0.108 0.197 0.128 −0.020 0.070 0.911

According to the connotation of the main component, the factors that have a greater influence on the waist–abdomen–buttock of female college students are hip girth, WHR, and WAD.

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3.2

59

Type Classification of Lower Part of Body Based on Feature Factors

According to the result of factor analysis, combined with the existing literature and the country standard of apparel size as well as the waist girth’s data of the actual sample, waist girth and each feature factor were analyzed by cluster analysis respectively, and the cluster number K was 5. The clustering results showed that types of lower body of female college students are relatively full, and HWD increases by 4 cm in turn, therefore the female’s hip shapes could be divided into four categories: flat hip, normal hip, feature hip, and super feature hip. In the same way, the clustering results of waist girth and WAD were analyzed, and the difference of WAD is 5 cm, which divided the female’s abdominal shape into four categories: flat abdomen, normal abdomen, convex abdomen, and special convex abdomen. The results were shown in Table 2. Based on the size change results of HWD and WAD, comprehensive cluster analysis was performed on waist girth, WAD, and HWD. Considering the difference and sample size, the number of clusters K was 9 and the clustering results were found in Table 3.

Table 2 Discrimination of abdominal types and hip types HWD

24

Hip shape WAD Abdominal shape

Flat hip 0–5 Flat abdomen

Normal hip 5–10 Normal abdomen

Feature hip 10–15 Convex abdomen

Super feature hip >15 Special convex abdomen

Table 3 Comprehensive clustering results of waist girth, WAD, and HWD Cluster

Waist girth

WAD

HWD

Proportion (%)

1 (Normal body) 2 (Special convex abdomen-super feature hip body) 3 (Flat abdomen-super feature hip body) 4 (Convex abdomen-feature hip body) 5 (Flat abdomen body) 6 (Feature hip body) 7 (Flat hip body) 8 (Flat abdomen body) 9 (Flat abdomen-flat hip body)

63.50 67.27

9.441 22.84

18.93 25.79

12.5 2.8

67.24 68.99 69.11 74.19 77.09 78.74 81.97

0.55 10.98 2.85 8.2 9.62 4.48 4.13

25.43 22.09 18.09 20.42 14.12 18.04 13.60

2.8 15.3 11.1 15.3 16.7 11.1 12.5

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The cluster analysis results of waist–abdomen–hip can be combined with Table 2 to show that WAD and HWD of Class 1 girls are both within the normal range, so they were named as normal abdominal normal hip body, referred to as normal body; the body type of Class 2 girls was relatively special, and the proportion was relatively small, waist girth was normal, but WAD and HWD were both large, which was named as special convex abdomen-super feature hip body. By analogy, other categories could be seen in Table 3. In summary, the shapes of the waist–abdomen–buttock of female college students were divided into the eight categories as shown in Table 3. According to their proportions, it could be seen that nearly half of the shapes of the waist–abdomen– buttock of female college students tended to be flat, while nearly one-third of the girls’ hips were slightly upturned.

4 Correlation Analysis of Lower Part of Body Type Factors 4.1

Correlation Analysis Between Waist Girth and Hip Girth

Waist girth and hip girth are the important dimensions in making trousers, and their size determines the fit of the trousers on the waist–abdomen–buttocks. Similar to the analysis of the waist–abdomen–buttock, cluster analysis was performed on WHD, Wb/Waist girth, and Hb/Hip girth, and the results were shown in Table 4. According to the results of cluster analysis, the difference between each type was about 4 cm, and as HWD increased, the ratio of Wb/Waist girth gradually decreased, and the proportion of Hb/Hip girth gradually increased. For the needs of trousers making plate, Table 4 was optimized to obtain the waist–hip-type judgment table, Table 5, which was used as a judgment rule for the data of waist girth and hip girth.

Table 4 Clustering results of waist girth and hip girth Cluster

HWD

Wb/Waist girth

Hb/Hip girth

Proportion (%)

1 2 3 4 5

10.938 14.606 18.264 21.972 25.990

0.490 0.484 0.482 0.482 0.480

0.506 0.506 0.509 0.509 0.511

6.9 23.6 36.1 27.8 5.6

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Table 5 Waist–hip-type judgment table HWD

28

Wb coefficient f1 Hb coefficient f2

0.50 0.505

0.49 0.506

0.484 0.506

0.482 0.508

0.482 0.509

0.481 0.511

0.48 0.512

Table 6 Regression equations of indicators on type of the lower body Circumferential direction variables and height (h), body mass index (BMI)

Length direction variables and H or h

Abdominal girth = 0.378 h + 2.1BMI − 22.128 Hip girth = 0.484 h + 1.865BMI − 23.814

Crotch depth = 0.16H + 8.48 Waist height = 0.719 h − 20.757 Thigh length = 0.2 h

Thigh circumference = 0.299 h + 1.446BMI − 25.377 Knee circumference = 0.205 h + 0.783BMI − 12.588 Calf circumference = 0.161 h + 0.774BMI − 6.774

4.2

Regression Analysis of Circumference Direction and Length Direction

Considering the control parts required for making trousers and the availability of daily body data, correlation analysis was performed on the following index variables: height (h), body mass index (BMI), hip girth(H), abdominal girth, thigh circumference, knee circumference, calf circumference, upper length, waist height, and thigh length. From the results of the correlation analysis of parts, the relationships between the regression equations were shown in Table 6.

5 Experimental Result Test Rule table of data generation could be obtained by the analysis results of the lower part of body factors. When the five easily measurable data such as height, weight, waist girth, hip girth, and knee circumference are obtained, the size of other parts will be calculated, as shown in Table 7. The data of the existing database was calculated and tested with relational equations of Table 7, and the results were compared with the data corresponding to variables in the database. The test results showed that due to the heterosexuality of the human body, some data had certain errors, but the error range was within 1 cm. When the pants are plated, the loose amount could be added according to the demand, so the calculation results of data generation table were valid.

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Table 7 Rules table of data generation Direct measurements

Calculation results

Height (cm) Weight (kg) Waist girth (cm) Hip girth (cm) Body mass index BMI Hip-waist difference HWD (cm) Waist height WH (cm) ½ back waist girth Wb (cm) ½ front waist girth Wf (cm) Crotch depth CD (cm) ½ back hip girth Hb (cm) ½ front hip girth Hf (cm) Thigh circumference T (cm) Thigh length TL (cm) Knee circumference N (cm) Calf circumference C (cm)

h Z W H BMI = Z/h2  104 H−W 0.719 h − 20.757 0.5f1W 0.5 W − 0.5Wb 0.16H + 8.48 0.5f2H 0.5H − 0.5Hb 0.299 h + 1.446BMI − 25.377 0.2 h 0.205 h + 0.783BMI − 12.588 0.161 h + 0.774BMI − 6.774

6 Conclusions In the paper, the three main components that have the highest contribution rate in the shape of the waist–abdomen–buttock of female college students are hip girth, waist-to-hip ratio, and waist–abdomen difference, and types of the waist–abdomen– buttock of female college students were divided into eight categories. The relationships between the circumference direction variables and the height and body mass index and the relationships between the length direction variable and the hip or height were obtained by regression analysis. The finding of the paper could provide the data basis of the human body for the rapid design of the fit comfort pants version. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhejiang Sci-Tech University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. WEI Heyue (2009) Ease value for apparel fit. In: Proceedings of the Fiber Society 2009 Spring Conference 2. Simmons K, Istook CL, Devarajan P (2004) Female figure identification technique (FFIT)for apparel part I: describing female shapes. J Text Apparel Technol Manage 4(1):1–16

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3. Vuruskan A, Bulgun E (2011) Identification of female body shapes based on numerical evaluations. Int J Clothing Sci Tech 23(1):46–60 4. Connell LJ, Ulrich P, Knox A et al (2002) Body scan analysis for fit models based on body shape and posture analysis. Natl Text Center Ann Rep 11(1):31–37 5. He T, Liu Y, Zhao X (2018) Body classification and prototype amendment of female college students in Tianjin. Wool Text J 46(07):53–57 6. Jiang C (2008) Pattern making system for men’s upper wear. Soochow University 7. Jing X, Li X (2017) Application of naive Bayesian method in girl’s figure discrimination. J Text Res 38(12):124–128 8. Pan L, Wang J, Sha S, Yu Z (2013) Study on body typing and garment size grading of young women in Northeast China. J Text Res 34(11):131–135 9. Zhongze Y (2000) Body and clothing. China Textile Press, China, pp 218–219

Correlation Study of Football Shin Guards Oppression and Muscle Fatigue During Sports Yifei Mu, Zimin Jin, Jing Jin, Yuhan He and Yuxiu Yan

Abstract With the popularization of sports and the increasing emphasis on physical health, the sports clothing industry has been promoted and developed. It also makes sports clothing functional and comfortable to meet higher professional requirements. The purpose of this study is to study the relationship between human body pressure and muscle fatigue caused by football leg protection. The methods used include documentation, experimental, subjective evaluation and mathematical analysis. With three football athletes as the research object, measuring its football shin guards wearing different pressures in running state, the calf part of clothing pressure numerical value, and a table facial electric tester and heart rate table for each were wearing different pressures of shin guards running fatigue dress for data collection. Comprehensive collation and correlation analysis combined with SPSS software, constructing the relationship between the clothing pressure of leg guards and muscle fatigue. Achieving more comfortable and more functional football leg guards provides theoretical basis and technical support. Open up a new way for the textile industry to better weave high-performance tight sportswear to alleviate wear fatigue.










Keywords Clothing pressure Wear fatigue Surface EMG index Football sock

1 Introduction In order to protect the human body, provide support for muscles and joints and reduce muscle shake during exercise, high-elastic fabric and tight-fitting shape exert a certain pressure on muscles, which is helpful for relieving muscle fatigue and

Y. Mu
Z. Jin (&)
Y. He
Y. Yan Zhejiang Sci-Tech University, Hangzhou, China e-mail: [email protected] J. Jin Hangzhou Vocational & Technical College, Hangzhou, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_8

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promoting recovery [1]. At present, there is a lot of research and practice on the aspects of clothing stress and muscle fatigue, and the relationship between clothing pressure and muscle fatigue for football leggings has not been studied. Using the surface electromyography (sEMG) tester and heart rate monitor to measure the pressure of football socks on calf gastrocnemius during running, collect relevant data and analyze the subjective evaluation of wear fatigue and obtained the correlation between garment pressure and muscle fatigue. In the design of related products, the wear pressure of the wearer can be reduced to a greater extent by controlling the clothing pressure in different parts. Provide theoretical basis and technical support for product development in fabric selection and pressure regulation of more comfortable and functional football leggings.

2 Clothing Pressure 2.1

Pressure Test Procedure

The pressure of clothing is the key factor affecting the comfort performance of the human body [2]. Clothing pressure is the vertical force exerted on the human skin due to the deformation of the fabric in the static or dynamic process due to the force of the body or the outside world being squeezed and stretched [3]. Considering the difference between the body and the part of the pressure perception, the comfort pressure of the garment ranges from 1.96 to 3.92 kPa [4]. Generally speaking, the comfort range of the human calf clothing pressure is less than 2.65 kPa. During strenuous exercise, the limit value of the clothing pressure that the human body can bear is about 1.96 kPa higher than the normal state. The comfort pressure of the leg guard in the experiment is ranged from 2.35 to 2.75 kPa [5]. Use MFF series multi-point membrane pressure test system to test the clothing pressure of the calf muscles of the calves of the experimental leggings of three subjects wearing different pressure gradients. Pick three young healthy male football players, as shown in Table 1. There was no history of injury to the ankle, ligament, muscle, and bones, and no vigorous exercise was performed within 24 h before the test. There is a certain relationship between fabric tensile elasticity and clothing pressure [6]. The experimental sample chooses Decathlon men’s soccer stockings with 98% polyester, 1% spandex, and 1% nylon. Overall use of plain weave, ribbon weave is used for the sock mouth and the heel, removal mesh is used for the surface of the Table 1 Basic situation of the tester

Number

Height (cm)

Weight (cm)

Calf circumference (cm)

1 2 3

162 180 180

110 180 145

36.4 40.2 38.7

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67

Fig. 1 Experimental socks

foot, as shown in Fig. 1, selects the common 39/41(S), 42/44(M), and 45/47(L) sizes for the comparison experiments of three different tightness levels. The muscles commonly used in the lower leg during running are the anterior tibial muscle in the front of the leg and the gastrocnemius muscle in the back of the leg. Considering the operability of the experiment and the pressure of the football socks on the muscles, the front part of the calf is affected by the barrier of the leg shield. The protrusion of two gastrocnemius muscles at the back of the leg was selected as the experimental experiment, as shown in Fig. 2. The pressure experiment is tested by MFF membrane pressure testing system, connect each part of the pressure test system. Paste the sensor sensing end on the test point of the model.

Fig. 2 Placement of electrodes

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Fig. 3 Pressure testing data of the bilateral gastrocnemius

Table 2 Grade evaluation of stress and comfort sensation rating Number

Stress S

Stress M

Stress L

Comfort S

Comfort M

Comfort L

1 2 3

2 3 3

2 2 2

2 2 2

2 2 3

2 3 2

2 3 2

2.2

Pressure Test Results and Analysis

The static pressure of the football socks under the three sizes of the three subjects was measured, and the pressure was converted into a pressure display according to the area of the induction wafer, which is about 0.785 cm2, the pressure test line diagram is obtained as Fig. 3. Set the pressure feeling level: 1—no pressure, 2—lighter, 3—moderate, 4— heavier, set comfort feeling level: 1—very uncomfortable, 2—all comfortable, 3— more comfortable, 4—very comfortable, get the grade evaluation as Table 2. The most comfortable stress is different for each participant. With the difference of compressive strength, duration of action and movement state, the subjective feeling of clothing pressure is also different. The tighter soccer socks have better supporting effect on muscles and higher comfort.

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3 Muscle Fatigue 3.1

Muscle Fatigue of Subjective Evaluation and Test Method

The most commonly used definition of exercise-induced muscle fatigue is the inability to maintain a specific level of strength during exercise [7]. The sEMG can effectively judge muscle fatigue and damage degree [8]. And, the sEMG signal changes significantly during exercise muscle fatigue [9]. EMG is a potential pattern produced by recording and displaying muscle activity, which is used to analyze muscle fatigue index [10]. By analyzing the changes of EMG data of lower limb muscles, we can know the quantity of motor units involved in activities and the discharge size of each motor unit in human muscles [11]. Use Hollies’ five-level interval scale as the criterion. Use the time– frequency joint analysis method [12], the root mean square (RMS) in the time– frequency index and the median frequency (MF) as the surface electromyography test index. Motion heart rate selects instantaneous heart rate in motion as test indicator Use the Delsys EMG works acquisition, and match the corresponded channels number with electrodes. Attach the matched surface EMG sensor to the four test positions on the lower leg and exposes the electrode, and keep the direction of the indicator arrow on the sensor consistent with the direction of the muscle fiber. Fix the electrode, put on the experimental leg guard, and experiment with treadmill. Accelerate from static uniform speed to 8 km/h, then maintain uniform motion, and start timing. The time of the experimental data collection is 5 min, and the interval of each running exercise is 12 min. Each participant wears three models and carries out three experiments, respectively.

3.2

Analysis of Fatigue Experiment Result

The results of EMG are shown in Fig. 4. It can be seen that the lateral calf muscle of the calf is smaller than the peak of the medial gastrocnemius electromyogram, the fluctuation is relatively larger, and the electromyogram of the leg protector is worn. The peak change is more gradual and smoother than the blank control group. During the running, the peak of the EMG gradually decreased with the increase of time. The peak of the EPC was relatively stable, the speed of the movement was basically maintained, and the fatigue was not obvious. In the subsequent stage, the peak of the EPC is relatively stable, the speed of motion is basically stable, and the fatigue is not obvious. The increase of clothing pressure has a mitigating effect on muscle fatigue, mainly concentrated in the middle and late stages of exercise.

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Fig. 4 Electrical experimental results

3.3

Statistical Analysis

Significant correlation analysis was performed on RMS values and subjective fatigue assessment scores using SPSS 13. 0 software, as Table 3. The greater the tightness of clothing, the more obvious the alleviation of gastrocnemius fatigue. The later the stage of fatigue occurs, the smaller the fatigue value of the whole exercise process. In the non-fatigue state, the MF value increases with the increase of the strength within a certain range, and the fatigue state MF shows a downward trend. By comparing the RMS at different times, fatigue time and fatigue degree can be determined. The RMS values decrease with increasing clothing pressure and have a high correlation.

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Table 3 Numerical interval and correlation of RMS and MF under different clothing pressure Number

Type

RMS numerical interval

RMS correlation

MF numerical interval

MF correlation

1

S

(2.084–3.434) *E − 05 (2.133–2.989) *E − 05 (1.899–2.102) *E − 05 (2.398–3.675) *E − 05 (1.865–2.887) *E − 05 (1.677–2.101) *E − 05 (2.273–3.150) *E − 05 (2.103–3.209) *E − 05 (1.646–2.990) *E − 05

0.558

(1.207–1.358) *E − 05 (1.133–1.289) *E − 05 (1.099–1.102) *E − 05 (1.090–1.275) *E − 05 (1.065–1.287) *E − 05 (0.977–1.101) *E − 05 (1.173–1.250) *E − 05 (1.103–1.209) *E − 05 (1.046–1.290) *E − 05

0.232

M L 2

S M L

3

S M L

0.532 0.569 0.484 0.639 0.628 0.321 0.376 0.385

0.467 0.305 0.394 0.549 0.220 0.471 0.305 0.285

4 Results and Discussion 4.1

Stress and Electromyography Experiment Conclusion

For the same subject, the smaller the size of the football socks, the greater the pressure on the human body and the two are negatively correlated. With the magnitude of the compressive strength, the length of the action time, the compression site and the state of motion, the subjective feelings of the human skin on the garment pressure are also different. Different people have different sensitivity to stress and comfort pressure. In the experimental electromyography index, the surface EMG indexes such as RMS and MF showed significant correlation with heart rate values and subjective fatigue. When the peak changes of EMG were significantly increased, the muscles began to fatigue. The subjective feeling of fatigue of the athletes is later than the fatigue time of the body. The RMS and MF values also determine that the muscles begin to fatigue in about two minutes. It is concluded that the occurrence of muscle fatigue is negatively correlated with garment pressure and indicating that garment pressure has a significant effect on muscle fatigue. Increasing garment pressure has a mitigating effect on muscle fatigue, and the magnitude of the relief effect varies from person to person.

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Conclusions

From the fields of motor neurology, ergonomics, physiology, and garment engineering, the correlation between clothing pressure and dress fatigue is revealed, and some theoretical and technical references are provided for the production of football socks and calf sports leggings. Apparel pressure has a significant effect on muscle fatigue. The increase in clothing pressure has a mitigating effect on muscle fatigue. To a certain extent, the greater the clothing pressure, the better the benign effect of delaying muscle fatigue, and the easier it is to relieve muscle fatigue. The greater the tightness, the more obvious the relief effect on the fatigue of the gastrocnemius muscle dressing so that the stage of fatigue state is delayed later, indicating that the fatigue value of the whole exercise process is smaller. When designing and developing calf sports leggings, garment enterprises can reduce the fatigue of the garment to a greater extent by controlling the difference in garment pressure. The research can continue to expand the test site, conduct more comprehensive and in-depth research on the impact mechanism of wear fatigue, and develop more high-performance sportswear. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhejiang Sci-Tech University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Fu W, Liu Y, Wei S et al (2011) Research advancements and prospects of compression equipments in sports science. China Sport Sci Technol 47(2):114–120 2. Yi Y (2008) Study of the pressure of knitted underwear. Master Dissertation of Tianjin Polytechnic University 3. Yue W, Wang G (2012) The influence of clothing pressure on the human body and its test methods. J Xi’an Polytech Univ 04:452–456 4. Na C (2009) Research on relationship between fabric elastics recovery and clothing pressure comfort by girdles. Master Dissertation of Dong Hua University 5. Wang X, Yao M (2001) The pressure comfort of sports protective equipment and functional exercise. J Northwest Inst Text Sci Technol 15(2):56–59 6. Li H (2010) Body-hugging seamless underwear shape standard abdominal pressure parameters. Knitting Ind 9:62–63 7. Liu H, Chen D, Wei Q (2010) Effect of clothing pressure on human physiology and objective testing. J Text Res 31(3):138–142 8. Zhang W (1990) Biomedical electronics. Tsinghua University Press, Beijing, pp 5–10 9. Xia W, Lou F, Gong B et al (2013) Determination of gastrocnemius fatigue electromyography college students after a long run. J Pract Tradit Chin Med 29(4):238–240

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10. Yang J, Li H (2011) Application status and prospects on the methods of electrical diagram in the evaluation of human movement. Shanxi Sports Technol 32(4):34–36 11. Wang W (2002) The study of tight clothing comfort. Shanghai Text Sci Technol 30(2):52–53 12. Chen J, Aming L, Wang G et al (2012) Effect of tight-fitting sportswear of different compression degrees on variation characteristics sEMG on vastus medialis during cycling motion. China Sport Sci 32(7):22–29

Influence of Wristband Tightness on the Protection of Wrist Joint in Table Tennis Mengyun Zhou, Zimin Jin, Jing Jin, Wenli Li and Yuxiu Yan

Abstract Table tennis is popular with most people. However, the research on the protective equipment wristbands for this sport only stays on the study of fabric properties. In order to study the tight comfort performance and protective performance of wearing wristbands in the table tennis ball and the relationship between them, fifteen female college students who love table tennis are the research subjects. The Qualisys Track Manager optical motion capture device was used to capture 3D data of the human body markers in the process of table tennis. The three-dimensional angle of the wrist was derived by visual 3D bone modeling. Mathematical statistical analysis and research of experimental data were conducted. The combination of compression comfort and injury protection is proposed, in order to propose a practical and systematic evaluation method of tight compression protection. The results show that the wrist tightness is an important factor for the wrist to have a good protective. When the optimal pressure range for wearing the wristband is controlled at 584.3–600 mN, it can protect the wrist and make the human body feel comfortable during exercise. Keywords Wrist tightness protective effect


Wrist angle
Comfortable range
Motion capture

1 Introduction Wrist is the most frequently used part of the body, which is an indispensable part of sports. At the same time, it is easy to be injured during exercise. Wearing a wrist protector can protect the wrist and reduce the probability of wrist sprain. Therefore,

M. Zhou
Z. Jin (&)
W. Li
Y. Yan Zhejiang Sci-Tech University, Hangzhou, China e-mail: [email protected] J. Jin Hangzhou Vocational & Technical College, Hangzhou, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_9

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people in the course of the campaign to improve the risk prevention of damage to the wrist strengthen the protection of the wrist. In table tennis, the wrist is the most important joint of the force. During the process of exerting force, the pressure on the wrist joint is the greatest [1]. Table tennis has the characteristics of quick response in a short period of time, which causes a great impact on the force parts and joints such as the wrist during the exercise process. The wrist joint is composed of many small bones, and the ability to withstand pressure is relatively poor. It is easy to cause damage to the wrist when hitting with a large force. There are certain technical requirements when playing table tennis. During the continuous serving and catching the ball, the wrist continues to receive the abduction quickly, flexing and stretching, and doing the spin rotation and external rotation, which greatly increases the probability of damage to the triangular cartilage disk in the wrist [2]. Therefore, it is necessary to study the protection of wrist injury in table tennis. Tight-fitting equipment is a kind of elastic fabric made of various parts of the body as a model. It applies pressure to various skin parts of the human body through different fabrics and different tightness to protect and cure certain parts of the human body [3]. Ibrahin [4] first defined the concept of the compression value of clothing, that is, the amount of contact pressure generated by the vertical application of the unit area of the surface of the human skin in the state of dressing. Nakagawa [5] and others analyzed the compression of the calf before and after the young and middle-aged women wearing tight pants. By analyzing different postures of volleyball, Xu et al. [6] designed and remade the structure and style of volleyball sportswear according to different compression ranges obtained from the experimental research results. However, in most studies on table tennis, there are few studies on the correlation between sports injury and tight compression of wrist protection. The tightness of the wristband has an important influence on the protection and comfort of the wrist. When the tightness is large, it is easy to cause physical exertion [7] and affects the physiological functions such as lymphatic, blood and nerve transmission and transmission of the human body [8]. When the tightness is small, not only the fixed protection is caused by the frequent changes of the body movement amplitude. The effect is greatly reduced, the wristband cannot protect the human bones, and even slides up and down as the exercise intensity increases, and there is no wearing comfort. Therefore, this paper will use three-dimensional dynamic capture and film sensing compression test to discuss the wrist injury during the process of table tennis from the perspective of the combination of damage protection and compression comfort and provide a reference for the development of tight-fitting wristbands.

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2 Experimental Design 2.1

Participants and Garment Information

A total of 80 healthy female college students aged 21–26, with good limbs and who love table tennis were selected from among the college students, and 15 female students who met the 160/84A medium-sized body generally accepted in GB/T1335-97 were selected [mean (SD) age, 22 (3) years, height (1.60 ± 0.13) m, weight (51.00 ± 3.00) kg, and wrist circumference (14.00 ± 0.90) cm]. Before experiment, all athletes were trained for standardized actions required. The most commonly used wearable knit wristbands were used in this study. The fabric has good elasticity and air permeability, with a fiber content of 55% nylon, 35% rubber, and 10% spandex. Three models of S, M, and L were selected for the comparative test of three different clothing pressures. The basic parameters of the specific experimental wristband are shown in Table 1.

2.2

Experimental Equipment

Qualisys Track Manager optical motion capture device. At present, motion capture is widely used in the motion and film industry [9]. In combination with the characteristics of the optical dynamic capture instrument, after a lot of preliminary experiments, Mark balls were attached to 12 bone markers of the subjects’ upper limbs, as shown in Fig. 1. A detailed description of specific marker locations is shown in Table 2. Germany MFF multi-point film sensing test system. At present, the study of clothing oppression in the dynamic process has become the mainstream of the current tight clothing oppression [10]. In the experimental test, the sensory compression sensor was attached to the three test points of the outer ulna USP (A), the medial humerus RSP (B), and the inner side of the wrist (C), and then covered with a wristband. Table 1 Experimental wristband parameters Knee number

Specifications

Length/cm

Surrounded degree/cm

1# 2# 3#

s. M L

8 8 8

16 17 18

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Fig. 1 Mark the ball

Table 2 Reference site for placing bone markers in Mark pellets (R: right; L: L)

2.3

Bone points tested

Location

R—USP R—RSP R—FAR L—USP L—RSP L—FAR

The right radial Right ulna Inside of right arm Left radius Left ulna Left medial arm

Experimental Procedures and Measurement

This experiment chooses in artificial climate chamber, the temperature control in (23 + 2) °C, and humidity control in (64 + 2)%. Firstly, mark small balls were affixed to the test site of the subjects, and then each subject was required to wear S, M, and L sports wristbands in turn to carry out table tennis backhand forehand attack. Two groups of experiments were carried out with each model of wrist guard. Each time the 60S was captured, and a stable 5S was selected for analysis. The pressure sensor is then worn and covered with a wristband to complete the stress test. Firstly, the skeleton model of the standing human body was built. Secondly, the dynamic movement model of table tennis was correlated with the static state model to establish a complete skeleton model of the upper limb. The 3D wrist angle data obtained by dynamic capture instrument were analyzed and derived by Visual 3D software. In this experiment, the subjective evaluation of the comfort of wristband was carried out during the exercise of the subjects wearing wristband with different

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Table 3 Evaluation grade of dressing pressure comfort 1

2

3

4

5

Very uncomfortable

More uncomfortable

General comfortable

More comfortable

It is comfortable

tightness. Factors such as fabric and style should be excluded in the evaluation, and the comfort of wristband tightness was mainly evaluated. The five-level interval evaluation scale was adopted as the standard for subjective evaluation, as shown in Table 3.

3 Results and Discussion The wrist joint is one of the most complex, functional, and flexible joints in the human body [11]. When playing table tennis, the wrist is mainly extended from the back to the adduction, the inner spin cuts the ball, the wrist in the continuous rapid extension, the action of the shot also includes the external rotation and yield action, and it constantly in different angles to move. Figure 2 shows the realization of X (flexion and extension), Y (extension), and Z (pronation, pronation, and extension) of the human wrist.

3.1

Correlation Analysis Between Wristbands Tightness and Wrist Angle

See Fig. 3 [12]. The three-dimensional space of the human body movement is divided into three dimensional planes: coronal plane, sagittal plane, and horizontal

Fig. 2 Three dimensions of wrist activity

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Fig. 3 Division of human movement space

plane. X represents the flexion and extension movement of the wrist joint around the coronal axis, Y represents the extension and extension movement of the wrist joint around the sagittal axis, and Z represents the rotation, inward rotation, and outward movement of the wrist joint around the vertical axis. From the point of view of studying the protection of tight compression, with the increase of the tightness of wrist protector, the change range of 3D angle of the wrist joint decreases, indicating that certain tight compression limits the maximum peak of the wrist joint activity. In addition, as the compression increases, the flexion and extension angle, the adduction and abduction angle and the rotation angle will also decrease correspondingly, which further verifies that the compression has a limiting effect on the movement of the wrist joint, thus controlling and fixing the wrist joint.

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Determination of Comfort Interval of Wristband

As can be seen from the results of one-way ANOVA, the explanatory variation of pressure is 89928.968, the variation caused by the sampling error is 4501.029, the significance level is 0.05, and the probability p is approximately 0, so it can be considered that tight compression has a significant impact on comfort evaluation.

3.3

Prediction of Armband Compression Threshold

In order to observe the change of comfort of the wrist joint under the compression of different degrees of tightness, the scatter diagram was made for the pressure value measured by the subject with wrist protector and the corresponding comfort evaluation, as shown in Fig. 4. When the pressure of the wrist joint was 600– 650 mN, the basic comfort could be achieved. When the pressure on the wrist joint is below 600 mN, it can achieve a more comfortable degree. So the combination of the wrist joint protection and comfortability determines the optimal tightness of table tennis tight campaign wristbands range of 584.3–600 mN.

Fig. 4 Scatter diagram of comfort evaluation under different pressure

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4 Conclusions Wrist protection tightness is an important factor for a good protective effect of the wrist. Wearing a certain degree of tightness of the wrist protection in order to ensure that the coronal surface of the wrist flexion and extension movement at the same time try to reduce the flexion and extension around the horizontal surface, sagittal axis, and vertical axis of the extension and extension of the pronation of the activity. With the increase of compression, the flexion and extension angle, adduction and abduction angle and rotation angle decrease correspondingly, which further explains that compression has a certain limiting effect on the movement angle of the wrist joint. When the tight pressure on the wrist joint is 584.3–600.6 mN, the wrist joint can be fixed and protected effectively. Combined with the comfort of the wrist joint, the optimal pressure range for wearing wrist protection in table tennis is determined to be 584.3–600 mN. In order to meet when playing table tennis can protect the wrist and make the human body feel comfortable. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhejiang Sci-Tech University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Guo SF (2000) Clinical anatomy of orthopedics. Shandong Science and Technology Press, Jinan, pp 542–573 2. Cao MS, Jiang GH, Tian L (2006) Investigation, analysis and research on wrist injury of gymnasts. J Nanjing Sport Inst 20(2):8–10 3. Fu WJ (2011) Research status and prospect of body-hugging equipment in the field of sports science. China Sport Sci Technol 47(2):62–69 4. Ibrahin SM (1985) A psychological scale for fabric stiffness. J Text Inst 76(6):44–47 5. Nakahashi M, Harumi T et al (1999) Lower leg front pressure behind degree. Jpn Res Assn Text End-uses 40(10):49–55 6. Xu J, Zhang L, Zhang F (2009) Research on pressure comfort of women’s beach volleyball apparel based on sports biomechanics. J Tianjin Polytech Univ 2:23–26 7. Dan BK, Kwon YH, Newton RU et al (2003) Evaluation of a lower body compression garment. J Sports Sci 21(8):601–610 8. Lu YH (2010) Effect and mechanism of dressing compression on skin blood flow of lower limbs. Suzhou University, pp 2–7 9. Yu XN (2013) On the application of motion capture technology in the process of film and television animation creation. Electron Technol Softw Eng 22:99–100

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10. Yin L, Zhang WB, Xia L (2008) Research review and analysis of clothing pressure comfort. J Text Res 29(3):137–142 11. Di XY (1996) Bone and joint injuries and diseases in the elderly. People’s Medical Publishing House, pp 39–40 12. Zhao LY, Huang SG, Sui LM et al (2015) Study on the difference of knee movement between treadmill walking and flat walking. J Harbin Eng Univ 36(9):1259–1260

Optimal Design of the Elastic Unit for the Serial Elastic Hip Joint of the Lower Extremity Exoskeleton Bingshan Hu, Guanming Cheng, Hongrun Lu and Hongliu Yu

Abstract This paper presents an optimal design method of the Elastic Unit for the Serial Elastic Hip Joint of the Lower Extremity Exoskeleton. The elastic element is a compact torsional elastomer. The design of the elastomer should meet the changes of the torque and stiffness of the hip joint during the movement of the human lower limbs. The design process is realized in two steps. Firstly, determining a basic element for the topology that meets the design criteria. Secondly, iterating in the ANSYS Workbench and optimizing its parameters to minimize the Von Mises Stress (making it less than the yield limit of the material used). After the theoretical results being calculated in the ANSYS Workbench, the torsional deformation angle of the elastomer is obtained by applying the torque simulation with different gradients. Besides, the experimental data is recorded and imported into MATLAB, and the stiffness curve is fitted by the least square method to verify whether the stiffness and linearity meet the design requirements. Finally, the simulation results of torsional elastomer can be obtained that the torque is 50 Nm, flexible Angle is 3°.




Keywords Series elastic actuator Lower extremity exoskeleton robot joint Elastomer Optimization design








Hip

1 Introduction Hemiplegia and paraplegia patients caused by stroke and spinal cord injury is increasing year by year. Hemiplegia and paraplegia patients can only stay in bed for a long time or participate in activities with the help of wheelchair, which bring a huge burden to the family and society. Therefore, many lower-limb exoskeleton robots have been developed at home and abroad to assist patients with daily walking and rehabilitation training, such as Rewalk, Fourier X1, Indego, etc. [1]. B. Hu (&)
G. Cheng
H. Lu
H. Yu Institute of Rehabilitation Engineering and Technology, University of Shanghai for Science and Technology, Shanghai, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_10

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Because the series elastic actuators have the advantages of low impedance, stable output force, shock absorption buffer and high power density, the application of the series elastic actuators in the lower limb exoskeleton robot will meet the requirements of flexible joint drive and increase the adaptability to the external environment [2]. Walking is the most basic motion requirement of human beings, so it is of great theoretical and practical significance to design and research SEA flexible drive of robot based on exoskeleton of lower limbs. Series elastic actuators are divided into linear series elastic actuators and torsional series elastic actuators. Due to the motion characteristics of human joint rotation, the torsional series elastic actuator is now widely used in the lower limb exoskeleton robot to assist the patients with stroke or the elderly in rehabilitation training and daily life [3]. In practical application, torsional series elastic actuators are connected in series between the motor and the harmonic reducer through a special torsional ring elastomer, and then the harmonic reducer drives the movement of human lower limb joints after amplifying the torque and regulating the speed through the transmission mechanism. The existing elastomer structures at home and abroad are mainly shown in Fig. 1. The inner ring and outer ring of the elastomer are connected through the elastic beam with deformation capacity to complete the torque transfer between the inner ring and the outer ring. However, the general transmission torque is small, and the torque must be increased by the transmission mechanism to drive the load, which increases the weight of the exoskeleton robot of the lower limbs, which is not conducive to patients’ wearing. Therefore, in this paper, a compact and lightweight elastomer is designed to directly drive the movement of the hip joint of the human body, eliminating the expansion of torque of the transmission mechanism and reducing the quality of the series elastic actuator, and its structure is optimized to make its mechanical strength meet the design requirements and ensure the linear stiffness.

Fig. 1 Typical elastomer design [3–5]

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Parameter

Value

Maximum torque Maximum deflection Outer ring diameter Inner ring diameter Stiffness

50 Nm 3° 69 mm 20 mm 954.93 Nm/rad

2 Analysis of Technical Indexes of Hip Joint Elastomer The purpose of this paper is to design a compact and lightweight rotatory elastomer for the hip joint, which can reduce the mass and space as much as possible, directly load the motor and the human hip joint, and then carry the torque load without amplification by the transmission mechanism. Considering the feasibility and individual differences (the maximum torque of hip joint during walking of some individuals may be slightly higher than 40 Nm), the design target of the maximum torque of the elastomer is set at 50 Nm. The actual physical stiffness values of the elastomers of the series elastic actuators were retrieved from literatures ranging from 100 to 1581 Nm/rad [3–5]. The applicability of these values has been proved by theoretical analysis and recent simulation studies [6]. In practice, the elastic body with small stiffness has large deformation, obvious non-linear stiffness and large hysteresis effect. In addition, it is easy to be deformed if used for a long time. In some literatures, elastomers [7] adopted multiple parallel connections of the same elastomers to transfer large torques, which increased the space volume, the probability of mechanism interference and the difficulty of overall layout. From what has been discussed above, the stiffness of 500–1000 Nm/rad was selected as the design target. When elastomers in 50 Nm torque loading, the deformation under 5° and adopt single chip load. According to the external dimensions of the connected harmonic reducer, the specific design parameters of the elastic components are shown in Table 1.

3 Optimum Design of Elastomer Structure 3.1

The Design of the Topology of the Elastomer

As shown in Fig. 2, the elastomer designed in this paper is mainly composed of an inner ring, an outer ring and three groups of symmetrically distributed elastic beams. The outer ring is connected to the flexible wheel of the harmonic reducer through the connecting wheel disc, and the inner ring is connected to the load directly through the output end cover. The inner and outer rings are connected by two groups of perfectly symmetrical elastic beams, of which the shape of the elastic beam is mainly arc. When the inner ring and outer ring rotate relative to each other,

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Fig. 2 Schematic diagram of elastomer structure

Outer ring

Elastic beam Inner ring

the elastic beam will produce elastic deformation so as to ensure that the elastic element can transfer torque and mitigate impact.

3.2

Optimization Process of Elastomer Structure

In the second step of elastomer design, finite element method (FEM) is used to optimize the size iteration design. The specific process is shown in Fig. 3. First of all, according to the use of elastic element in hip joint, there are N kinds of corresponding structural parameters to design its structural form T. Secondly, a structure is selected, and the optimization parameters and their range are set. It is assumed that the number of optimization parameters is M, and the parameter range of the parameter i is (xmin, xmax), forming an m-dimensional parameter search space. Take a set of values in the parameter search space and use SolidWorks for parametric modelling, and then import the parameterized CAD model into the finite element software. In this paper, the ANSYS workbench is used for finite element analysis to find whether the elastic element meets the design index, and finally obtain the optimized structure that meets the design index through iteration.

3.3

Optimization Process of Elastomer Structure

Elastic deformation of elastic beam in elastomer is the main source of rotational deformation. In order to make the stiffness value of elastomer meet the design index, its shape needs to be optimized. Because the elastomer is connected to the harmonic reducer and the load, the inner and outer ring dimensions have been fixed. The span and camber of the elastic beam determine the distribution of the load, but in order to ensure that the elastic beam does not interfere with the inner ring and outer ring of the elastomer, the upper and lower boundaries of the elastic beam are respectively moved by a fixed distance. In order to avoid too many parameters

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Fig. 3 Optimization flow of elastomer structure

leading to too complicated optimization analysis and calculation, the distances of R1, R2 and R3 of the local loop of elastic beam are fixed, and the places where the directions are changed are connected with smooth tangential circles. The parameters finally determined for optimization include: elastomer thickness t, a single set of elastic beam span a, and elastic beam width b, as shown in Fig. 4. In the case of ensuring no interference during the deformation process between the elastic beams, the parameter values range are: t = 7–15 mm, a = 70°–90°, b = 1.5–2.5 mm. According to the above major optimization variables, the response surface optimization design provided by ANSYS workbench software is used for optimization analysis. The response surface optimization design method calculates the corresponding response results according to the different values of input parameters in its variation range, and then obtains the influence of the values of each parameter on the results.

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Fig. 4 Elastomer parameter definition diagram

It can be seen from Figs. 5, 6 and 7:

8 7 6 5 4 3

1.5

2 1

2 10

Thickness (mm)

15 2.5

8.5 8 7.5 7 6.5 6 5.5 5 4.5 4 3.5 3 2.5 2 1.5 1

Equivalent Stress Maximum (×103Mpa)

Rotation angle (Degree)

1. When a and t are constant, the flexible rotation angle and maximum stress generated by the elastic element decrease with the increase of elastic beam thickness b. 2. When a and b are constant, the flexible rotation angle and maximum stress generated by the elastic element decrease with the increase of elastomer thickness t.

2.8 2.6 2.4 2.5

2.2 2

2

1.8 1.6

1.5

1.4

1 1.5 2

Beam width (mm)

2.5

10 11 12 13 14 15

9

8

7

1.2 1 0.8 0.6

(×103)

Fig. 5 The influence of different values of b and t on the rotation angle and maximum stress of elastic elements when a = 80°

4.5

Rotation angle (Degree)

4 4.5 3.5 3.5

3

2.5

2.5 2

1.5

10

70

75

80

85

Beam span (Degree)

1.5

Equivalent Stress Maximum (×103Mpa)

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1.9 1.8 1.7 1.6 1.5 1.4

1.5

1.3

1

70

90 15

75

80

85

Beam span (Degree)

10 11 12 13 14 90 15

9

8

7

1.2 1.1 1 0.9 0.8

6

Rotation angle (Degree)

5.5 6

5 4.5

5

4

4

3.5 3 1.5 2.5

3 2 70

2 75

80

85

Beam span(Degree)

90 2.5

2 1.5

Equivalent Stress Maximum (×103Mpa)

Fig. 6 The influence of different values of a and t on the rotation angle and maximum stress of elastic elements when b = 2 mm

1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1

1.5

1

1.5

1 0.9

70

2 75

80

85

Beam span(Degree)

0.8

90 2.5

Fig. 7 The influence of different values of a and b on the rotation angle and maximum stress of elastic elements when t = 11 mm

3. When t and b are constant, the flexible rotation angle and maximum stress generated by the elastic element increase with the increase of elastic beam span a. 4. When the safety coefficient is 1.2 and the maximum stress is below 1100 Mpa, the final optimization analysis and calculation result is: t = 13.89 mm, b = 1.79 mm, a = 88.3°. Under this condition, the finite element analysis results of the elastomer are shown in Fig. 8. As can be seen from Fig. 8, when the output torque is 50 Nm, the maximum stress and the maximum flexible rotation angle of the elastic member are 1060 MPa and 3.0493°, which are considered to satisfy the design requirements.

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Fig. 8 Results of finite element analysis

4 Simulation Verification of Elastomer Structure When the output torque is 50 Nm, the flexible rotation angle of the elastomer reaches the maximum, and the shape of the elastic element is preliminarily determined by the optimal design. Considering the nonlinear problem of spring stiffness, in order to ensure the consistency of the stiffness of the elastic element under different loads, the stiffness simulation analysis of the optimized elastic element was carried out, that is, the deformation under different output torque was analyzed. When using the ANSYS workbench for analysis, a fixed constraint was added to the inner ring of the elastomer, and the outer ring was added with a torque constraint, wherein the torque constraint was increased by a gradient of 5 Nm, and the torque was applied in the range of −50 to 50 Nm (the positive direction of the torque was the positive direction of the middle Z axis). The rotation angles of the elastomer under different loading torques were obtained, as shown in Table 2. The data in the above table were imported into MATLAB, and the above table data were fitted by the least square method to obtain the stiffness curve of the elastomer, as shown in Fig. 9.

Table 2 Corresponding table of elastomer torque and flexible rotation angle Ti

Rotation angle h(°)

Load torque T (Nm)

Rotation angle h(°)

−50 −45 −40 −35 −30 −25 −20 −15 −10 −5

−3.0493 −2.7444 −2.4394 −2.1345 −1.8296 −1.5246 −1.2197 −0.91479 −0.60986 −0.30493

50 45 40 35 30 25 20 15 10 5

3.0493 2.7444 2.4394 2.1345 1.8296 1.5246 1.2197 0.91479 0.60986 0.30493

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Fig. 9 Fitting curve of flexible rotation angle of elastomer with torque change

3

Deformation (°)

2 1 0 -1 -2 -3 -4 -50 -40

-30 -20

-10

0

10

20

30

40

50

Torque (Nm)

It can be seen from Fig. 9 that under the action of different torques with equal gradient, the flexible rotation angle of the elastomer has a good linear relationship with the corresponding load torque, and its stiffness is consistent under different loads. According to Hooke’s law, the stiffness of the elastic element is: K = 939.49 Nm/rad, in line with the pre-design goals.

5 Conclusion In this paper, a structural optimization design scheme of torsion elastic unit is proposed. The maximum withstand torque is 50 Nm and the maximum flexible deformation angle is 3°. It is suitable for compact and lightweight series elastic actuators. The elastomer directly acts on the output to drive the load and is connected to the motor through the harmonic reducer. The design index can meet the requirement of the series elastic drive applied to the lower extremity exoskeleton robot to drive the hip joint movement. After determining the elastomer topology, the parametric CAD model of elastomer was established and imported into ANSYS workbench for optimization design, and the theoretical results were finally calculated by ANSYS workbench. According to the theoretical results, the CAD model of elastomer is re-established, and then the simulation verifies whether the deformation of elastomer meets Hooke’s theorem and ensures the linear stiffness of elastomer. The simulation proves that the elastic structure satisfies the design index and proves the correctness of the elastic structure design.

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References 1. Hurst J, Rizzi A, Hobbelen D (2004) Series elastic actuation: potential and pitfalls. In: International conference on climbing and walking robots 2. Veneman JF, Ekkelenkamp R, Kruidhof R et al (2006) A series elastic-and bowden-cable-based actuation system for use as torque actuator in exoskeleton-type robots. Int J Robot Res 25(3):261–281 3. Yang J (2014) Control method and experimental research on elastic actuation of exoskeleton robot. Master’s thesis of Harbin Institute of Technology 4. Robinson DW (2000) Design and analysis of series elasticity in closed-loop actuator force control. Doctoral dissertation of Massachusetts Institute of Technology 5. Tagliamonte NL, Sergi F, Carpino G et al (2010) Design of a variable impedance differential actuator for wearable robotics applications. In: 2010 IEEE/RSJ international conference on intelligent robots and systems, IEEE, pp 2639–2644 6. Carpino G, Accoto D, Sergi F et al (2012) A novel compact torsional spring for series elastic actuators for assistive wearable robots. J Mech Des 134(12):121002 7. Kim S, Bae J (2014) Development of a lower extremity exoskeleton system for human-robot interaction. In: 2014 11th international conference on ubiquitous robots and ambient intelligence (URAI), IEEE, pp 132–135

Analysis About the Influence of Protective Equipment on the Upper Limbs’ Range of Motion Chenming Li, Tianhao Wang and Yuhong Shen

Abstract In order to study the influence of protective equipment on the upper limbs’ range of motion, 40 healthy males were selected as subjects to wear short-sleeved sportswear, firefighting suits, chemical protective suits, and explosion-proof suits, respectively, so as to test the range of motion of upper limb shoulder joints, hand joints, and the wrist joint. Eight joint activity parameters were selected, and the effects of various protective equipment on the upper limb’s range of motion were analyzed by comparing the angle of motion with the short-sleeved sportswear and referring to the fast upper limb evaluation method. It was manifested through the analysis results that the explosion-proof suits have the greatest influence on the upper limb’s range of motion, and there are significant differences in the shoulder joint, elbow joint, and wrist joint. The firefighting suits have less influence on the upper limb’s range of motion, which mainly on the shoulder joints. Keywords Range of motion


Spine
Biomechanics

1 Introduction Protective equipment can block the attacking to the human body from physical, chemical, and biological factors, and ensure the life safety of personnel. Domestic and foreign scholars have conducted a lot of researches on the performance test of protective equipment materials and the overall performance test of suits currently, but the research about the influence of protective equipment on the human body range of motion is rare. C. Li (&)
Y. Shen The Quartermaster Research Institute of Engineering and Technology, Beijing 100010, China e-mail: [email protected] T. Wang Southwest Hospital, Third Military Medical University, Chongqing 400038, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_11

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Tochinaray [1] and others made research on the demand for Japanese firefighting suits, and the results showed that firefighters have a higher demand for high flexibility in clothing. Patton et al. [2] pointed out that the huge volume and hard material of chemical protective suits have a negative impact on human joint movements. Saul et al. [3] pointed out that with the increase in the number of protective clothing, the movement flexibility of the human body decreased. Hu et al. [4] pointed out that the ergonomic performance of protective clothing should meet the mechanical demand of human body movements, that is, the mechanical performance of protective clothing should be consistent with the freedom degree of human body movement, the range of motion, and the torque at the joints of the human body. In study of protective clothing ergonomic performance, Coca et al. [5] evaluated the three aspects of the subject’s range of motion, operational flexibility, and comfortability. The joint activity is also called the range of motion (ROM), which refers to the motion arc or angle through which the joint moves [6]. By measuring the degree of human body joint activity while wearing protective equipment, the extent and range of the reduction of the joint moving function in the wearing state can be assessed. According to the position of joints, joint activities can be divided into activities of upper limb joints, lower limb joints, and trunk joints. Upper limb joint activities include joint activities at shoulder, elbow, wrist, and finger; lower limb joint activities include joint activities at hip, knee, and ankle. According to the path of motion, joint activities can be divided into sagittal activity (such as shoulder flexion and extension), coronal movement (shoulder abduction), and horizontal movement (shoulder joint horizontal adduction). The research of joint mobility of protective equipment mainly focuses on the measurement and analysis of the angle of joint movement under static dressing status.

2 Test Design 2.1

Subjects

40 young men were selected as subjects for joint mobility test. The age range of the subjects ranged from 17 to 24 years old, with an average of 20.4 years old; the height ranged from 168 to 180 cm with an average of 173.9 cm; and the weight ranged from 55 to 86 kg with an average of 66 kg. The subjects were healthy and had no bone or muscle injury.

2.2

Test Subjects

The tested subjects were divided into two groups, one group wore protective equipment, including firefighting suits, chemical protective suits, and explosion-proof suits, and the other group was a control group, which wore short-sleeved sports top and shorts.

Analysis About the Influence of Protective … Table 1 Upper limb joint mobility test parameters

2.3

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Serial number

Joint name

Movement

1 2 3 4 5 6 7 8

Shoulder joint

Antexion Back extension Abduction Bending Back dorsiflexion Palmar flexion Ulnar flexion Radial flexion

Elbow joint Wrist joints

Test Equipment

The test is conducted using a joint mobility measurement system. The system is tested by a third party and the measurement accuracy is ±0.1°.

2.4

Test Parameters

The upper limb joint mobility test mainly focused on the shoulder joint, elbow joint, and wrist joint. The measurement parameters are shown in Table 1.

3 Test Result Analysis The data of the eight upper limb joint activity angle parameters of the subjects wearing the firefighting suits, the chemical protective suits, and the explosion-proof suits were, respectively, compared with the parameters of subjects wearing light clothing for the test. The results are shown in Tables 2, 3, and 4. From the paired t-test results of the firefighting suit (Table 2), it can be seen that there are no significant differences (p > 0.05) in the three parameters of the wrist joint back dorsiflexion, wrist joint ulnar flexion, and wrist joint radial flexion. The other five parameters had a significant difference (p < 0.05). From the average data, there are significant differences in joints of light clothing that are more flexible than firefighting suits, and their differences range from 4.1° to 8.5°. The joint motion restraint of firefighting on shoulder and elbow is significantly larger than that on wrist. From the paired t-test results of the chemical protective suit (Table 3), it can be seen that, among the eight parameters, except for the wrist joint ulnar flexion which has is no significant difference (p > 0.05), the other seven parameters have reached significant differences (p < 0.05). Because the protective clothing uses a fully enclosed structure, the protective gloves and the garment are integrated, which restricts the wrist joint mobility. From the average data, the joints with significant

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Table 2 Statistical results of firefighting suit Measurement parameter

1 2 3 4 5 6 7 8

Shoulder joint abduction Shoulder joint antexion Shoulder joint back extension Elbow joint bending Wrist joint back dorsiflexion Wrist joint metacarpal flexion Wrist joint ulnar flexion Wrist joint radial flexion

Average value (°) Light Firefighting clothing suit

Difference

t

176.7 180.3 62.3

168.2 176.1 57.2

8.5 4.2 5.1

8.313 3.651 2.792

0.000 0.001 0.008

144.4 54.3

136.8 52.0

7.6 2.3

4.877 1.097

0.000 0.279

66.9

62.8

4.1

3.010

0.005

40.2 25.6

40.0 23.9

0.2 1.7

0.113 1.219

0.910 0.230

Table 3 Statistical results of chemical protective clothing Measurement parameter

1 2 3 4 5 6 7 8

Shoulder joint abduction Shoulder joint antexion Shoulder joint back extension Elbow joint bending Wrist joint back dorsiflexion Wrist joint metacarpal flexion Wrist joint ulnar flexion Wrist joint radial flexion

Average value (°) Light Firefighting clothing suit

Difference

t

176.7 180.3 62.3

166.2 168.3 52.4

10.5 12 9.9

6.01 4.51 4.35

0.000 0.000 0.000

144.4 54.3

126.4 47.7

18 6.6

10.53 3.11

0.000 0.003

66.9

53.6

13.3

7.09

0.000

40.2 25.6

39.3 17.8

0.9 7.8

0.47 5.49

0.640 0.000

differences are more common clothing which has large joint mobility than the chemical protective clothing, and their differences range from 6.6° to 18°. For the main joints of the upper limbs, the effect of chemical protective clothing on joint mobility is greater than that of firefighting suit. From the paired t-test results of the explosion-proof suit (Table 3), it can be seen that among the eight parameters of the statistics, the three parameters of wrist joint back dorsiflexion, wrist joint ulnar flexion, and shoulder joint back extension have no significant differences (p > 0.05). The other five parameters reached a significant difference (p < 0.05). From the average data, the joints with significant differences are the joints of the light clothing which have greater joint mobility than that of the

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Table 4 Statistical results of the explosion-proof suit Measurement parameter

1 2 3 4 5 6 7 8

Shoulder joint abduction Shoulder joint antexion Shoulder joint back extension Elbow joint bending Wrist joint back dorsiflexion Wrist joint metacarpal flexion Wrist joint ulnar flexion Wrist joint radial flexion

Average value (°) Light Firefighting clothing suit

Difference

t

176.7 180.3 62.3

135.5 146.6 61.5

41.2 33.7 0.8

23.12 10.78 0.412

0.000 0.000 0.682

144.4 54.3

108.2 53.3

36.2 1.0

14.36 0.45

0.000 0.653

66.9

56.6

10.3

6.49

0.000

40.2 25.6

39.5 22.0

0.7 3.6

0.46 2.30

0.646 0.027

explosion-proof suits. The difference between them varies from 3.6° to 41.2°, the wrist joint radial flexion difference is the smallest, and the shoulder joint abduction difference is the largest.

4 Evaluation Method of Joint Mobility Reference to the Rapid Up Limb Assessment (RULA) for each joint posture angle range assessment; it determines the evaluation criteria for protective clothing flexibility by using the measured joint mobility data. The higher the score, the less flexible the clothing is, and the greater the uncomfortableness, the more the clothing needs to be improved. In the first step, the measured value of each joint angle of the protective clothing is compared with the measured value of the corresponding joint angle of the common clothing, and if there is a significant difference (p < 0.05), the difference shall be calculated. In the second step, the evaluation scores for the shoulders, elbows, and wrists are determined according to Table 5. For example, for the shoulder joint antexion, if there is no significant difference after being compared with the common clothing, the score is 0. If there is a significant difference, the difference shall be further calculated, and the score shall be determined according to the corresponding difference range. The upper limb joint mobility scores of various protective equipment were calculated according to the different range, the firefighting suit was 6 points, the chemical protective suit was 11 points, and the explosion-proof suit was 12 points. From the perspective of test results, the impact of the firefighting suit on the upper limb joint mobility is relatively small, and the explosion-proof suit has the greatest impact, which is mainly affected by the heavy structure of the explosion-proof suit itself.

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Table 5 Score determined according to the difference between the joint angle of the protective clothing and the common clothing Position

Joint

Index

Comparison value

Shoulder

Antexion

Range of difference Score Range Score Range Score Range Score Range Score Score Range Score Score

0°–15° 1 0°–20° 1 0°–15° 1 0°–15° 1 0°–15° 2 2 0°–15° 1 1

Back extension Abduction Elbow

Bending

Wrist

Back dorsiflexion Palmar flexion Ulnar flexion Radial flexion

15°–30° 2 >20° 2 15°–30° 2 15°–30° 2 >15° 3 3 >15° 2 2

30°–45° 3

>45° 4

30°–45° 3 30°–45° 3

>45° 4 >45° 4

5 Discussion The influence of protective equipment on the joint mobility of the upper limbs directly affects the operational performance of the equipment. The effects of three protective equipment on upper limb’s range of motion were compared and analyzed with the absence of external loads. The following explorations will be carried out in future research: (1) Combine joint mobility test with typical working conditions. Different protective equipment have different application conditions. For example, fire fighting suit needs to deal with the high-temperature environment of the fire field, and the explosion-proof suit is mostly used for statistic kneeling posture or lying posture. Subsequent researches will differentiate the need for joint activity in different conditions and give different evaluation weights to each joint. (2) Research and evaluation on the joint activity of protective equipment under virtual reality simulation condition. With the development of virtual reality technology, it is possible to develop a simulation system which is capable of simulating the wearer’s whole body motion and providing the wearer with an immersive virtual simulation scene with a stronger sense environment feeling. Digital human modeling technology puts digital people into a virtual environment and controls their execution and completion of test tasks, thereby completing an ergonomic evaluation of indicators such as motion trajectory and accessibility, etc.

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(3) Combine the joint activity evaluation with physiological evaluation. While affecting physical activity, the protective equipment also affects human physiological activities (such as cardiovascular function and cardiopulmonary function). Therefore, these indicators can be included in the evaluation range of protective equipment ergonomic performance, so that a summary evaluation index system can be established.

References 1. Tochinaray CC, Fujita M et al (2005) Protective clothing-related heat stress on firefighters in Japan. Environ Ergon XI: 39 2. Patton JF, Bidwell TE, Murphy MM et al (1995) Energy cost of wearing chemical protective clothing during progressive treadmill walking. Aviat Space Environ Med 66:238–242 3. Saulev EV, Jaff J (1995) The effects of clothing on gross motor performance. US Army Quartermaster Research and Development Command 4. Hu H, Ding L, Yang C et al (2007) Investigation on ergonomics characteristics of protective clothing based on capture of three-dimensional body movements. Digit Hum Model 4561:856– 864 5. Coca A, Roberge R, Shepherda A et al (2008) Ergonomic comparison of a chem/bio prototype firefighter. Eur J Appl Physiol, 104(2): 351–359 6. Roger B, Shawn D, Gail L (2010) A protective firefighter turnout suit. Int J Occup Saf Ergon, 16 (2):135–152

Biomechanical Study of Long-Segment Spine Instrumentation: The Effect of Cross-Links Tianhao Wang, Chenming Li and Yan Wang

Abstract Objective To develop FE models of osteotomized spine and evaluate whether cross-link (CL) improves the instrumentation stiffness and decrease the risk of complications. Methods Firstly, a finite element model without CL was established based on CT images of postoperative male patients with thoracolumbar kyphosis. Secondly, five models were established according to the different numbers and positions of CL. Four loading conditions (flexion, extension, lateral bending, and axial rotation) were applied to the model. The range of motion (ROM), the maximum value and distribution of the implants, and vertebrae stress were compared between models. Results With number of CL increasing, the ROM of instrumented segments was reduced. When loading axial rotation condition, the ROM was reduced by 21.98%. The peak stresses were located on rods during axial rotation, on proximal pedicle screws during flexion, and on the osteotomy site during extension and lateral bending. The CLs had an effect of dispersing stress concentration. Conclusions The application of CLs is able to enhance the rigidity of the construct. With the number of CL increasing, the ROM of the construct is reducing, especially in axial rotation. CLs can also make stress concentration dispersed. Keywords Finite element analysis Cross-link


Spine
Biomechanics
Osteotomy


T. Wang
Y. Wang (&) Department of Orthopaedics, General Hospital of Chinese People’s Liberation Army, Beijing 100853, China e-mail: [email protected] C. Li The Quartermaster Research Institute of Engineering and Technology, Beijing 100010, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_12

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1 Introduction Pedicle screw and rod instrumentation system have been widely used and shown to provide satisfying correction and stabilization while achieving a high fusion rate and clinical outcome. Especially the following osteotomy in spinal deformity, long-segment instrumentation is necessary to maintain the correction. A cross-link (CL) is designed to enhance the fixation strength and stability [1]. However, the use of CL is still under debating, and the advantage is less well understood. A large amount of biomechanical studies were performed to determine whether CLs provide any additional benefit [2–7]. These studies demonstrated that CLs can provide additional stiffness and torsional rigidity. Meanwhile, it also benefits for maintaining correction and producing a stiffer fusion mass. On the contrary, Wood et al. [2] tested an industrially fabricated spine model and showed CLs did not provide significant additional rotational stiffness. Valdevit et al. [4] found CL provided no differences in torsional stiffness in the thoracic porcine spine. In a multicenter cohort study of AIS, the clinical or radiographic outcomes were not improved by CLs. The previous studies seldom focused on instrumented spine following osteotomy. According to Schwab’s classification [8], the osteotomy above Grade 3 destroys the stability of three columns and reconstructs spinal sequence by the instrumentation system. Schwab 3 osteotomy, such as pedicle subtraction osteotomy and vertebral column decancellation, is a common osteotomy technique to correct spine thoracolumbar deformity. Considering the spine instability caused by osteotomy, therefore, the stiffness and reliability of internal fixation is more important in this kind of cases. Biomechanical studies are able to provide reliable data. But the force response of each part is hard to evaluate to some extent. Therefore, the former studies mainly concentrated on the CL’s effect on the stiffness of fixation. The finite element (FE) analysis is able to comprehensively demonstrate the stress change on both fixation and spine caused by CLs. The objectives of this study were to develop FE models of the osteotomized spine and evaluate whether CLs improve the instrumentation stiffness and decrease the risk of complications including fracture and fixation failure. Furthermore, the optimal number and distribution of CLs were also studied.

2 Materials and Methods 2.1

Patient and Surgery

A patient (male, 165 cm, 49 kg) with thoracolumbar kyphotic deformity was included in this study. This patient underwent spinal osteotomy, namely vertebral column decancellation [9] (Schwab 3), at L1 and the spine was fused from T10 to L4 with pedicle screw and rod system without CL.

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Development of the FE Model of Instrumented Spine

The FE model of the spine was reconstructed from the postoperative CT images. The scanning slice thickness was 0.5 mm, and 434 tomographic pictures including spine from T1 to sacrum were imported into MIMICS 17.0 (Materialise NV, Leuven, Belgium) to reconstruct images of each vertebra. The reconstructed images were imported into 3-Matic 9.0 (Materialise NV, Leuven, Belgium) to develop the three-dimensional geometric model of the spine. Then, the geometric model was imported into ICEM-CFD (ANSYS Inc., Canonsburg, PA, USA) and meshed in a combination of hexahedral elements and shell elements. The material properties were taken from published literature and are shown in Table 1 [10, 11]. The major spinal ligaments representing in the FE model included anterior longitudinal ligament, posterior longitudinal ligament, intertransverse ligaments, ligamentum flava, supraspinal ligament, and interspinous ligament. The ligament was mainly subjected to tensile stress, and its strength was related to the number of fibers in the direction of loading. The elastic coefficients of ligaments in the model were taken from the experiment by Yoganandan et al. (Table 2). A posterior fixation system with pedicle screws (diameter = 6.5 mm, length = 45.0 mm) and rods (diameter = 5.5 mm) was modeled using hexahedral elements. The pedicle screws and rods were made of titanium alloy with a density of 4.5 g/cm3, Young modulus of 110 MPa, and Poisson ratio of 0.3. Finally, the FE model without CL (nCL) was well developed (Fig. 1a).

Table 1 Material properties of finite element model [6, 7]

Cortical bone Cancellous bone End plate Endplate cartilage Nucleus pulposus Annulus fibrosis Cartilage

Element type

Material model

Material properties

Shell

Power-law plasticity Power-law plasticity Power-law plasticity Isotropic elastic Viscoelastic

q = 1.83 g/cm3, E = 16,700 MPa, v = 0.3, k = 440.8 MPa, n = 0.2772 q = 1.0 g/cm3, E = 291 MPa, v = 0.3, k = 7.118 MPa, n = 0.2741 q = 1.83 g/cm3, E = 5567 MPa, v = 0.3, k = 146.9 MPa, n = 0.2772 q = 1.68 g/cm3, E = 25 MPa, v = 0.4

Hexahedron Shell Shell Hexahedron

K = 2.2GPa, Gs = 2 MPa, Gl = 1.4 MPa

Isotropic q = 1.2 g/cm3, E = 3.4 MPa, v = 0.49 elastic Shell Isotropic q = 1.68 g/cm3, E = 10 MPa, v = 0.4 elastic q indicates density. E indicates Young modulus. v indicates Poisson ratio. k indicates strength coefficient. n indicates strain-hardening exponent. K indicates volume model Hexahedron

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Table 2 Definition of ligament elasticity coefficient in male adult Ligament

ALL

PLL

IL

LF

SL/ISL

Elasticity coefficient(N/mm) 21.34 36.42 19.96 26.78 10.04 ALL indicates anterior longitudinal ligament. PLL indicates posterior longitudinal ligament. IL indicates intertransverse ligaments. LF indicates ligamentum flava. SL indicates supraspinal ligament. ISL indicates interspinous ligament

Fig. 1 Development of FE model

2.3

Development of the FE Model of Spine with CLs

The CL was simplified as a horizontal rod which solid connected bilateral rods. The model and material properties were the same as the rods in the fixation system. Four fixation configurations were modeled: one CL at osteotomy site (CL-1), one CL at osteotomy site and another at proximal segment (CL-2P), one CL at osteotomy site and another at distal segment (CL-2D), one CL at osteotomy site, and other two at both proximal and distal segments (CL-3) (Fig. 1).

2.4

Validation of the Intact Model

To validate the intact spine model, the range of motion (ROM) of segments from L2 to L5 of the intact spine model was compared with the literature [12, 13]. The translational and rotational degree of freedom of L5 was constrained. Torque of 10 Nm was applied on L2 to simulate the load of lateral bending, anterior flexion, and extension.

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Assessment Indexes

The biomechanical effects of CL were analyzed. Stress distribution of the pedicle screws, rods, CLs and vertebrae of five FE models under flexion, extension, lateral bending, and axial rotation were measured. The biomechanical differences between five FE models could be compared.

2.6

Loading and Boundary Conditions

The FE model from T1 through the entire sacrum spine was used for analysis. The contact nodes of the sacrum were defined to be rigidly fixed, and the loads were applied on the upper surface of T1 end plate. A compressive load of 280 N acted to the upper surface of T1, which corresponded to the partial weight of the human body. To simulate different conditions such as flexion, extension, lateral bending, and axial rotation, the moment of 10 Nm was applied to the upper end plate of T1.

3 Results 3.1

Model Validation

ROMs of the intact segments were compared with results of prior FE and experimental studies in similar loading conditions. In flexion, extension and lateral bending, the model data were within the range of previous studies. The calculated ROM for L2-L3, L3-L4, and L4-L5 is shown in Table 3.

3.2

ROM of Different Constructs

The ROM of the fixed T10-L4 segments for all constructs was tested and is presented in Fig. 2. With the number of CL increasing, the ROM of instrumented Table 3 Comparison of the range of motion Flexion/(°)

Extension/(°)

Lateral bending/(°)

Model 1

Model 2

Model 3

Model 1

Model 2

Model 3

Model 1

Model 3

Model 2

L2-L3

3.86

3.28

5.4

2.97

2.32

3.3

4.77

3.31

5

L3-L4

3.06

3.58

6.1

2.12

1.18

2.3

3.47

3.33

4.3

L4-L5

3.58

4.49

7.1

2.56

3.89

4

4.01

2.08

3.8

Model 1 is the intact model in this study. Model 2 is the model in the study of Shirazi-Adl. Model 3 is the model in the study of Yamamoto

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Fig. 2 Comparison of ROM of T10 to L4 segments between five constructs in flexion, extension, lateral bending, and axial rotation

segments was reduced by 2.37, 1.89, and 2.49% in flexion, extension lateral bending in average, respectively. When loading axial rotation condition, the ROM was reduced by 21.98%. With the number of CL increasing, the ROM tended to be limited. The ROM in CL-2P was less than CL-2D.

3.3

Stress Distribution on nCL

Under axial rotation, the peak stress of the entire model was 118.3 MPa on rods. In flexion, the proximal pedicle screws were the part of stress concentration with 221.1 MPa. When it came to extension and lateral bending, the point of peak stress came to L1, the osteotomy site, with 47.11 and 60.2 MPa, respectively. The peak stress on rods, screws, and L1 vertebra in different conditions is demonstrated in Fig. 3.

3.4

Impact of CLs Number on Stress Distribution

The stress concentration was dispersed to other components with the use of CLs. In axial rotation, the stress on rods was reduced by CL. With the CLs number increasing, the stresses were reduced to 96.10, 105.30, and 113.20 MPa in CL-1, CL-2P, and CL-3, respectively, which were still smaller than nCL. The stress on L1 vertebra was reduced, whereas the stress on screws was increased. In flexion, the stress concentration on screws was decreased by 17.73% in CL-1, 19.86% in

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Fig. 3 Distribution of stress on finite element model (nCL), rods, pedicle screws, and L1 vertebra during: a Flexion. b Extension. c Lateral bending. d Axial rotation

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Fig. 4 Graphical representation of peak stress on different part of finite element model varies with number of CLs increasing during: a Flexion. b Extension. c Lateral bending. d Axial rotation

CL-2P, and 17.00% in CL-3 compared to nCL. The stress on rods was slightly increased in CL-2P and CL-3. In extension, the stresses on screws, rods and L1 vertebrae were decreased by CLs. Especially on L1 vertebra, the stress concentration part, CL-2P, had the greatest impact on stress reducing. In lateral bending, CL-2P reduced stress concentration on L1 vertebrae when CL-1 and CL-3 made the stress increasing. The stress on rods was decreased when CL number adding. Greater stress on screws was showed in CL-1 and CL-2P (Fig. 4).

4 Conclusions There are two advantages of CLs. Firstly, the application of CLs is able to enhance the rigidity of the construct. With the number of CL increasing, the ROM of the construct is reducing. The CLs have the best behavior of increasing the stability for construct under axial rotation. Another advantage is that CLs make the stress concentration dispersed. Comparing various CLs configurations in different motion conditions, we recommend that the optimal method is to place two CLs at both osteotomy site and proximal segment. Further clinical studies are required to evaluate the impact of CLs on clinical outcomes.

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References 1. Lehman RA, Kang DG, Wagner SC, Paik H, Cardoso MJ, Bernstock JD et al (2015) Biomechanical stability of transverse connectors in the setting of a thoracic pedicle subtraction osteotomy. Spine J 15:1629–1635 2. Wood KB, Wentorf FA, Ogilvie JW, Kim KT (2000) Torsional rigidity of scoliosis constructs. Spine (Phila Pa 1976) 25:1893–1898 3. Brodke DS, Bachus KN, Mohr RA, Nguyen BK (2001) Segmental pedicle screw fixation or cross-links in multilevel lumbar constructs. A Biomech Anal Spine J 1:373–379 4. Valdevit A, Kambic HE, McLain RF (2005) Torsional stability of cross-link configurations: a biomechanical analysis. Spine J 5:441–445 5. Kuklo TR, Dmitriev AE, Cardoso MJ, Lehman RA, Erickson M, Gill NW (2008) Biomechanical contribution of transverse connectors to segmental stability following long segment instrumentation with thoracic pedicle screws. Spine (Phila Pa 1976) 33:E482–487 6. Alizadeh M, Kadir MR, Fadhli MM et al (2013) The use of X-shaped cross-link in posterior spinal constructs improves stability in thoracolumbar burst fracture: a finite element analysis. J Orthop Res 31(9):1447–1454 7. Liao JC, Chen WP, Wang H (2017) Treatment of thoracolumbar burst fractures by short-segment pedicle screw fixation using a combination of two additional pedicle screws and vertebroplasty at the level of the fracture: a finite element analysis. BMC Musculoskelet Disord 18:262 8. Schwab F, Blondel B, Chay E, Demakakos J, Lenke L, Tropiano P, et al (2015) The comprehensive anatomical spinal osteotomy classification. Neurosurgery 76(Suppl 1):S33–41 9. Wang Y, Lenke LG (2011) Vertebral column decancellation for the management of sharp angular spinal deformity. Eur Spine J 20:1703–1710 10. Holzapfel GA, Schulze-Bauer CA, Feigl G, Regitnig P (2005) Single lamellar mechanics of the human lumbar anulus fibrosus. Biomech Model Mechanobiol 3:125–140 11. Gzik M, Wolanski W, Tejszerska D (2008) Experimental determination of cervical spine mechanical properties. Acta Bioeng Biomech 10:49–54 12. Shirazi-Adl SA, Shrivastava SC, Ahmed AM (1894) Stress analysis of the lumbar disc-body unit in compression. A three-dimensional nonlinear finite element study. Spine (Phila Pa 1976) 9:120–134 13. Yamamoto I, Panjabi MM, Crisco T, Oxland T (1989) Three-dimensional movements of the whole lumbar spine and lumbosacral joint. Spine (Phila Pa 1976) 14:1256–1260

Microexpression Recognition Training in Left-Behind Children in China Xueling Zhang, Lei Chen, Gaojie Fan, Huajie Sui and Xunbing Shen

Abstract The left-behind children could have impairment in emotional expressions recognition. A microexpression recognition training tool developed by the authors was used to address the possible emotional recognition deficits of left-behind children. Forty middle school students participated in the study; half of them were left-behind children. They received the microexpression recognition training and took surveys of Interpersonal Reactivity Index and the Big Five Personality Inventory. The results showed that (1) the microexpression training was equally effective for left-behind children and non-left-behind children in China; (2) the left-behind children had an advantage recognizing spontaneous microexpressions; (3) girls perform better than boys after microexpression recognition training while conducting microexpression training tool (METT) task; (4) the personality trait of openness had a close relationship with microexpression recognizing, and fantasy of Interpersonal Reactivity Index (IRI) had a significant positive partial correlation with gain score of METT test. The current results indicated there was no impairment of emotional expressions recognition in left-behind children. The study also showed the effectiveness of a Chinese version of microexpression training tool designed for Asian adolescents. Keywords Microexpression training tool Personality


Left-behind children
Empathy


X. Zhang
L. Chen
H. Sui
X. Shen (&) Jiangxi University of Traditional Chinese Medicine, Nanchang 33004, China e-mail: [email protected] G. Fan Miami University, Oxford 45056, USA © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_13

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1 Introduction Every year, Chinese rural-to-urban migrant population migrate to the cities in search of economic opportunities to support their families, which resulted in thousands of children are left behind. The parent–child separation creates many emotional problems in left-behind children, who often struggle with a sense of abandonment, feeling sad, and alone, without emotional support provided by parents [1]. These emotional problems impede the interpersonal communication of left-behind children [2], who lack self-confidence while meeting people, have low interpersonal trust, and do not have the intent to communicate. It is vital to recognize other’s emotion during the interpersonal communication [3]. Expressions of emotions are clues about others’ internal experience of emotions and serve as a social signal that offers clues about another person’s appraisal of their situation and their likely actions. People who are good at recognizing emotional expressions have a better social adjustment, better school performance, and even better workplace success across a wide range of industries and job types [4]. The deficits in emotional expressions recognition have been linked to poor social and community functioning. Some studies found that the left-behind children were impaired in emotional expressions recognition [5]. The training of microexpression can improve the ability to recognize emotions [6]. Microexpression is a fleeting expression, usually lasts for 0.2 s at longest [7, 8], which reflects the internal true emotional feeling of people. There are some attempts to use the microexpressions training to improve the recognition of emotion [9]. The results are positive; microexpression training does enhance the ability of emotion recognition. Inspired by the seminal studies, some researchers use the microexpressions training tool on patients with impaired emotional function [10, 11]. We conducted a study of training of emotion recognition in left-behind children to address their possible emotion recognition problems. The original microexpression training tool was developed by Ekman [7], in which the facial expressions were selected from Western models. There is an in-group advantage while recognizing emotional expressions, namely that accuracy tends to be higher when perceiving emotions expressed by members of the same versus different cultural group. Therefore, we developed a microexpression training tool which used the picture of expressions selected from Asian models (see details below).

2 Method 2.1

Participants

Forty students were recruited from a local middle school located in the rural area nearby Nanchang city of Jiangxi Province. Twenty left-behind children (10 male, mean age = 12.8 years, SD = 0.63, and 10 female, mean age = 12.2 years,

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SD = 0.78) lived with grandparents and twenty non-left-behind children (10 male, mean age = 12.1 years, SD = 0.74, and 10 females, mean age = 12.4 years, SD = 0.52). Permission from supervising teachers has been obtained to conduct the experiment.

2.2

Procedure

The experiment was conducted on the same day for each student, who completed the task on a computer with mouse response. The microexpression training started with the completion of the pretest measure (as described below). Next, the training was carried out. Then the posttest measures were administrated. Before performing the experiment, the experimenter explained the confidentiality, showed how to do the task, and told them that they have the right to terminate and quit the experiment anytime if they wanted. At the end of the microexpression training, the participants completed the Chinese version of Interpersonal Reactivity Index (IRI) [12] and the Big Five Personality Inventory [13]. The participants were given a gift while finished all tasks. Raw data from E-Prime were transferred to Microsoft EXCEL software and then used SPSS for statistical analysis.

2.3

Microexpression Training Tool

The study used a tool which was adapted from a previous Chinese version of microexpression training tool developed by the authors [14]. In the part of pretest, we added microexpression recognition, which included nine microexpression video clips (two videos for disgust, two videos for happiness, two videos for sadness, two videos for surprise, and one video for fear) chosen from CASME II [15]. The training was the same as the previous one. In the posttest, nine microexpression video clips were added. The procedure of the training was illustrated in Fig. 1.

Fig. 1 Illustration of the design of microexpression training. ART affect recognition test, METT microexpression training tool, Micros microexpression video clips, IRI Interpersonal Reactivity Index, BFI Big Five Personality Inventory

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3 Results 3.1

The Difference of Microexpression Recognition Ability

A 2 groups (left-behind children and non-left-behind children)  2 genders (male, female)  2 test (pretest, posttest) mixed design, repeated measures analysis of variance (ANOVA) was conducted with the participants’ accuracy score (%) entered as the dependent variable. For METT, the main effect of group and gender was not significant [F (1, 36) = 0.003, p = 0.956, η2p < 0.001; F (1, 36) = 0.08, p = 0.779, η2p = 0.002]. There was a significant main effect for test [F (1, 36) = 46.514, p < 0.001, η2p = 0.564] (Fig. 2). The interaction of test and gender was significant [F (1, 36) = 4.777, p = 0.035, η2p = 0.117] (Fig. 3). No other interactions attained significance. For Micros, the main effect of gender was not significant [F (1, 36) = 0.776, p = 0.384, η2p = 0.021]. There was a significant main effect for test and group [F (1, 36) = 9.709, p = 0.004, η2p = 0.212; F (1, 36) = 5.130, p = 0.030, η2p = 0.125] (Fig. 2). The interaction of test and gender was marginal significant [F (1, 36) = 3.496, p = 0.070, η2p = 0.089]. No other effects were significant. Considering a more straightforward, parsimonious manner, we compared the gain scores between posttest and pretest in the part of METT and micros separately. For METT, the results showed that the accuracy of the left-behind children increased from the pretest (M = 50.7%, SD = 9.5%) to posttest (M = 72.1%, SD = 13.3%); paired sample t-test found that the difference of posttest and pretest is significant (t (19) = 6.38, p < 0.001). The accuracy of the non-left-behind children increased from the pretest (M = 53.9%, SD = 15.1%) to posttest (M = 69.3%, SD = 14.9); paired sample t-test found that the difference of posttest and pretest is significant (t (19) = 3.44, p < 0.003). Though the gain score is much higher for left-behind children than non-left-behind children, the independent sample t-test showed no difference on gain scores between them (t (38) = 1.086, p = 0.285).

Fig. 2 Left panel: accuracy of the recognition scores of the pretest and posttest. The error bars indicate the standard errors. Right panel: The main effect of group while recognizing microexpression in video clips, the accuracy of left-behind children is significantly higher than that of non-left-behind children. The error bars indicate the standard errors

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Fig. 3 Interaction between the gender and test. In the part of METT, the interaction is significant (see details in text). The error bars indicate the standard errors

For Micros, the accuracy of the left-behind children increased from the pretest (M = 38.3%, SD = 17.1%) to posttest (M = 45.61%, SD = 18.0%); paired samples t-test found that the difference of posttest and pretest is not significant (t (19) = 1.748, p = 0.097). The accuracy of the non-left-behind children increased from the pretest (M = 27.2%, SD = 15.1%) to posttest (M = 36.6%, SD = 15.3%); paired sample t-test found that the difference of posttest and pretest is not significant (t (19) = 2.602, p = 0.018). T-test on gain scores showed no difference (t (38) = 0.404, p = 0.688) between left-behind children and non-left-behind children. Though there is no difference on the gain scores, the results of ANOVA showed that the main effect of group is significant (Fig. 2).

3.2

The Difference in Empathy and Personality

The mean scores of IRI for the left-behind and non-left-behind children were 32.7 and 33.3 points. There was no significant difference between the two groups (p > 0.05). The mean scores of Big Five Personality Inventory for the left-behind and non-left-behind children were 66.15 and 63.55 points. There was a marginal significant in the agreeableness (p = 0.051). No other significant differences were found (all ps > 0.05).

3.3

The Relationship Between Microexpression Recognition, Empathy, and Personality

Scores of each participant on the subscales of IRI (perspective taking, fantasy, empathic concern, and personal distress) and BFI (extraversion, agreeableness, conscientiousness, neuroticism, and openness) were entered into multiple

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regression models as independent variables. A series of multiple regressions assessed the relation between these subscales and the following dependent variables: (1) pretest (aim to find the individual difference characteristics of recognizing emotion); (2) gain scores (aim to find the individual difference characteristics of learning emotion knowledge). Linear regression analysis found that openness had a significant partial correlation with scores of Micros1, i.e., the ability of recognizing microexpressions in videos (Beta = −0.439, R2 = 0.200, p = 0.019); fantasy had a significant positive partial correlation with gain score of METT test (Beta = 0.393, R2 = 0.188, p = 0.028); and personal distress had a marginally significant negative partial correlation with gain score of METT test (Beta = −0.306, R2 = 0.188, p = 0.066). No other significant correlations were found.

4 Discussion 4.1

The Microexpression Recognition Ability in Left-Behind Children and Non-left-Behind Children

The results showed that microexpression recognizing training was effective for both groups. As could be seen from Fig. 2, both groups had their ability to recognize microexpressions improved from the pretest to posttest except the left-behind children didn’t show a significant improvement while recognizing spontaneous microexpression in videos (marginally significant). No difference in gain scores between two groups suggested that learning emotion knowledge of the two groups is not different. The mixed design ANOVA found that there was a significant difference between left-behind children and non-left-behind children while recognizing spontaneous microexpressions. As showed in Fig. 2, the left-behind children were much better at recognizing microexpressions compared with non-left-behind children, which was contrary to what we thought before. The results indicated there was no impairment in emotional expressions recognition in left-behind children. The cause of this could be that left-behind children experienced more neglects and had to pay more attention to others to acquire concerns during interpersonal communication, which resulted in their higher ability at detecting subtle cues to emotion. Research [16] did find a female advantage in the recognition of emotional facial expressions. In the current study, there was no main effect of gender; however, the interaction between gender and test was significant while doing the METT task. As could be seen from Fig. 3, girls could get more benefits from the training though they have a little bit lower ability to recognize artificial microexpression at pretest using METT task.

Microexpression Recognition Training in Left-Behind …

4.2

119

The Microexpression Recognition, Empathy and Personality in Left-Behind Children and Non-left-Behind Children

The current study found that the personality trait of openness had a close relationship with the ability to recognize spontaneous microexpressions. There was some evidence of a relationship between macro expression recognition and the personality traits of openness [17]. Our finding showed openness to new experiences was also an important trait for recognizing microexpression, which no previous study tested. Fantasy of IRI (taps respondents’ tendencies to transpose themselves imaginatively into the feelings and actions of fictitious characters in books, movies, and plays, e.g., “I really get involved with the feelings of the characters in a novel”) had a significant positive partial correlation with gain score of METT test, put another way, someone with higher fantasy score could do better at recognizing the artificial microexpression. The current results showed there were no differences in empathy and personality between the left-behind children and the non-left-behind children. Therefore, the left-behind children did not meet the stereotype that their left-behind environment would make their emotional development worse. The results might be partly due to that the participants were sampled in an urban–rural fringe area, which made the environment they grew up is almost the same. In summary, the current research found the microexpression training was equally effective for left-behind children and non-left-behind children in Chinese. The left-behind children had an advantage of recognizing spontaneous microexpressions. Girls perform better than boys after microexpression recognition training while conducting METT task. The personality trait of openness had a close relationship with microexpression recognizing. The fantasy of IRI had a significant positive partial correlation with gain score of METT test. In the future, we need to test the microexpression recognition training tool to bigger samples and populations with established impairment of emotional recognition (Autism, patients with traumatic brain injury, and so on). The neural mechanisms underlying the current results also should be studied. Acknowledgements This project was partially supported by a grant from the Planed Project of Social Sciences in Jiangxi Province (Project No. 18JY24), the Project of Humanities and Social Sciences in Colleges and Universities of Jiangxi Province (XL17105), and the National Natural Science Foundation of China (No. 31460251). Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Jiangxi University of Traditional Chinese Medicine. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Ayala T (2017) Children, “Left Behind”: exploring the nexus of migration and formal education in Mexico. Washington Western Washington University, Bellingham 2. Fan F, Su L, Gill MK, Birmaher B (2010) Emotional and behavioral problems of Chinese left-behind children: a preliminary study. Soc Psychiatry Psychiatr Epidemiol 45(6):655–664 3. Ekman P (2007) Emotions revealed: recognizing faces and feelings to improve communication and emotional life. Macmillan, New York 4. Hall JA, Andrzejewski SA, Yopchick JE (2009) Psychosocial correlates of interpersonal sensitivity: a meta-analysis. J Nonverbal Behav 33(3):149–180 5. Ge Y, Zhong X, Luo W (2017) Recognition of facial expressions by Urban internet-addicted left-behind children in China: an eye-movement study. Psychol Rep 120(3):391–407 6. Matsumoto D, Hwang HS (2011) Evidence for training the ability to read microexpressions of emotion. Motiv Emotion 35(2):181–191 7. Shen X, Wu Q, Fu X (2012) Effects of the duration of expressions on the recognition of microexpressions. J Zhejiang Univ-Sci B 13(3):221–230 8. Shen X, Wu Q, Zhao K, Fu X (2016) Electrophysiological evidence reveals differences between the recognition of microexpressions and macroexpressions. Front Psychol, 7 9. Svetieva E, Frank MG (2016) Empathy, emotion dysregulation, and enhanced microexpression recognition ability. Motiv Emotion 40(2):309–320 10. Russell TA, Chu E, Phillips ML (2006) A pilot study to investigate the effectiveness of emotion recognition remediation in schizophrenia using the micro-expression training tool. Br J Clin Psychol 45(4):579–583 11. Zhang X, Chen L, Zhong Z, Sui H, Shen X (eds) (2017) The effects of the micro-expression training on empathy in patients with schizophrenia. international conference on man-machine-environment system engineering. Springer 12. Siu AM, Shek DT (2005) Validation of the interpersonal reactivity index in a Chinese context. Res Soc Work Practice 15(2):118–126 13. Soto CJ, John OP (2017) The next big five inventory (BFI-2): developing and assessing a hierarchical model with 15 facets to enhance bandwidth, fidelity, and predictive power. J Pers Soc Psychol 113(1):117–143 14. Chen L, Shen X, Yang H (eds) (2018) Micro expression recognition training in college students. In: 2018 first asian conference on affective computing and intelligent interaction (ACII Asia): IEEE 15. Yan WJ, Li XB, Wang SJ, Zhao GY, Liu YJ, Chen YH et al (2014) CASME II: an improved spontaneous micro-expression database and the baseline evaluation. Plos One 9(1) 16. Forni-Santos L, Osório FL (2015) Influence of gender in the recognition of basic facial expressions: a critical literature review. World J Psychiatry 5(3):342–351 17. Matsumoto D, LeRoux J, Wilson-Cohn C, Raroque J, Kooken K, Ekman P et al (2000) A new test to measure emotion recognition ability: Matsumoto and Ekman’s Japanese and caucasian brief affect recognition test (JACBART). J Nonverbal Behav 24(3):179–209

Research on the Relationship Between Personality and Speed Skills Training of Military Academy Cadets Nan Men, Qi Gong, Cheng Jin, Haitao Zhao, Pengdong Zhang and Zhibing Pang

Abstract Purpose To study the relationship between personality and performance in speed skill training of cadets in military academies. Methods The personality traits of 30 students randomly selected from a military academy were tested with the Cattell 16 Personality Factor Questionnaire. Pearson’s correlation analysis in SPSS 20.0 software was used to analyze the correlation between the test results and speed skill training results. Results The susceptibility of human beings has a significant influence on the training of speed skills. Conclusion Military academy teachers should pay attention to and give full play to the personality characteristics of the cadets in speed skill training, so as to improve the training effect. Keywords Character


Speed skill training
Relationship research

1 Introduction To study the relationship between cadets’ individual personality factors and speed skill training, this paper makes full use of the theory of human-machineenvironment system engineering [1] and carries out a 16PF test on 30 cadets of a military academy, including the gregariousness, intelligence, stability, aggressiveness, excitability, perseverance, daring, sensitivity, suspicion, fantasy, privateness, anxiety, experimentation, independence, self-discipline, tension and other indicators. At the same time, 30 cadets achieved three times of speed skills training and achieved average results. Through the analysis, the relationship between personality index and speed skill training results is obtained, which provides reasonable suggestions for military academy teachers to carry out targeted teaching and training. N. Men
C. Jin
H. Zhao (&)
P. Zhang
Z. Pang Zhengzhou Campus, CPLA, Army Artillery and Air Defence Forces Academy, Zhengzhou 450052, China e-mail: [email protected] Q. Gong College of Mechanical Engineering, Zhengzhou University, Zhengzhou 450000, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_14

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2 Objects and Methods 2.1

Objects

Thirty students (random numbers 1–30) were randomly selected from local high school graduates of a military academy for testing, all male. The average age of the participants was 23 years old, and their height ranged from 168 to 184 cm, with an average height of 175.83 cm.

2.2

Experimental Materials

The personality traits were tested with the Cattell 16 Personality Factor Scale (16PF) [2]. Statistical analysis software SPSS 20.0 was used as the analysis tool [3].

2.3 2.3.1

Method Personality Character Test

The test is organized by professionals, and the questionnaire is answered at a unified time. The participants should complete the demonstration exercises independently for no more than one hour. The valid answer sheet is counted out as the original score and transformed into the standard score between 1 and 10 by norm [4].

2.3.2

Speed Skills Test

Thirty subjects were given speed skill training performance test three times, one-week interval between each test and take the average score of the three tests and take min as the unit. In order to ensure the authenticity and comprehensiveness of the experimental data, the author also consulted the record data of the speed skill training of the students’ physical fitness files. Through comparative analysis, the author finally took the average of the three in situ speed skill training results for the next experimental analysis.

3 Data Statistics and Analysis The results of the basic data of 16 Personality Factors test of the subjects are shown in Table 1. The results of speed skill training are shown in Table 2.

7

5

7

9

7

7

9

6

6

7

10

6

7

9

6

6

7

6

6

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

7

5

9

10

4

7

8

3

7

9

2

6

5

Gregariousness

1

No.

7

8

7

7

6

3

6

8

7

8

5

8

5

9

8

6

9

8

9

9

10

5

7

8

5

7

Intelligence

7

8

3

6

8

5

5

7

6

4

6

9

5

10

3

4

5

5

3

3

8

5

7

3

5

6

Stability

Table 1 Cattell’s 16 Personality Factor test results

7

6

3

4

7

6

7

7

6

5

6

9

6

8

4

4

8

7

6

4

9

9

4

8

9

6

Aggressiveness

9

9

1

4

7

10

6

10

7

2

9

7

4

9

6

1

6

6

6

1

10

5

7

7

9

2

Excitability

Perseverance

5

5

5

2

8

5

2

7

5

5

9

9

1

9

3

7

3

8

5

6

6

6

6

2

5

5

9

6

4

5

8

6

6

8

7

6

9

7

3

10

5

6

5

7

6

6

7

6

8

5

8

5

Daring

Susceptibility

(continued)

5

4

8

5

3

5

3

6

6

5

4

3

7

2

6

4

5

3

4

3

3

2

2

8

6

1

Research on the Relationship Between Personality… 123

7

Suspicion

5

2

3

6

3

3

4

5

6

6

6

7

2

5

2

5

2

4

5

9

5

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

6

29

No.

10

28

30

8

Gregariousness

27

No.

Table 1 (continued)

Intelligence

6

7

6

5

5

6

8

5

4

4

5

7

4

6

5

2

3

3

5

6

5

Fantasy

7

7

7

10

10

10

8

10

6

7

8

10

8

4

6

8

10

7

6

8

7

5

4

6

9

Privateness

1

5

3

6

Stability

7

4

3

6

8

5

2

6

2

7

5

7

4

7

8

4

6

5

5

5

4

Anxiety

10

6

9

7

10

4

10

9

Excitability

5

5

6

6

6

5

7

5

6

5

7

5

5

7

6

6

8

8

6

4

5

Experimentation

Aggressiveness

Perseverance

1

2

5

5

9

5

7

6

5

7

7

6

6

6

9

3

9

6

4

1

6

Independence

3

7

3

5

5

4

7

5

4

8

10

4

8

3

6

4

6

6

4

8

6

6

2

5

4

Self-discipline

7

4

8

8

Daring 8

5

8

5

5

7

6

4

5

4

8

7

8

5

6

9

3

8

4

8

5

5

(continued)

5

2 Tension

Susceptibility 5

124 N. Men et al.

Suspicion

5

5

6

5

6

4

5

2

9

No.

22

23

24

25

26

27

28

29

30

Table 1 (continued)

Fantasy

6

5

6

6

5

5

8

4

4

5

7

8

7

9

8

10

6

5

Privateness

Anxiety

7

2

9

4

4

5

7

6

4

Experimentation

3

6

7

6

5

6

8

4

6

Independence

1

6

4

4

6

5

6

3

5

2

7

4

5

8

5

5

2

5

Self-discipline

Tension

8

2

7

6

2

7

8

7

9

Research on the Relationship Between Personality… 125

126

N. Men et al.

Table 2 Speed skills training achievements of subjects No.

First test

Second test

Third test

Average score

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

3.11 4.11 3.32 3.17 3.06 3.59 3.15 3.13 3.12 3.43 3.22 3.25 3.18 3.19 3.20 3.29 4.03 3.40 3.54 3.14 3.29 3.29 3.35 3.26 3.40 2.52 3.17 3.40 3.27 3.38

3.20 4.00 3.26 3.20 3.09 3.43 3.17 3.11 3.13 3.41 3.19 3.19 3.17 3.24 3.19 3.42 4.13 3.41 4.00 3.26 3.33 3.16 3.40 3.37 3.42 2.50 3.18 3.33 3.03 3.34

3.12 3.43 3.45 3.25 3.00 3.40 3.21 3.22 3.14 3.32 3.37 3.29 3.12 3.15 3.07 3.39 4.00 3.39 4.02 3.28 3.38 3.31 3.41 3.18 4.06 3.08 3.14 3.45 3.12 3.58

3.14 3.85 3.34 3.21 3.05 3.47 3.18 3.15 3.13 3.39 3.26 3.24 3.16 3.19 3.15 3.37 4.05 3.40 3.85 3.23 3.33 3.25 3.39 3.27 3.63 2.70 3.16 3.39 3.14 3.43

Pearson’s correlation analysis in SPSS 20.0 software was used to analyze the correlation between the results of 16 Personality Factors and the results of speed skill training. The results are shown in Table 3. In analysis Table 3, select one of the personality factors and speed skill training has the highest correlation degree of significant difference, and it is considered that this factor affects the speed skill training performance of the tested personnel [5]. Therefore, we can get the correlation between the susceptibility of the personality factors and the training of speed skills. The psychological qualities required for speed skill training are shown in Table 4.

Experimentation

Anxiety

Privateness

Fantasy

Suspicion

Susceptibility

Daring

Excitability

Excitability

Aggressiveness

Stability

Intelligence

Gregariousness

0.234

0.213

Significance (bilateral)

0.047

Pearson correlation

Significance (bilateral)

0.039

0.434

0.148

0.514 0.494

0.130

0.000

0.200 −0.720**

0.241

0.190

−0.246

0.377

0.862

Significance (bilateral)

0.010 −0.380*

−0.124

−0.167

−0.033

Pearson correlation

0.366*

0.611

0.540

Significance (bilateral)

Pearson correlation

0.413 −0.097

0.709

−0.116

Significance (bilateral)

Pearson correlation

0.653 −0.155

0.036

−0.071

Significance (bilateral)

0.009 −0.464**

0.581

0.466**

0.002

0.538**

0.075

0.330

0.396

0.161

−0.086

0.105

Pearson correlation

0.384*

0.792

Significance (bilateral)

Pearson correlation

0.050

0.105

Pearson correlation

0.074

−0.302

Pearson correlation

Significance (bilateral)

0.696

0.957

0.331

Significance (bilateral)

0.010

0.779

0.184

0.847

Significance (bilateral)

0.053

0.517

Pearson correlation

0.037

0.356

Significance (bilateral)

Pearson correlation

0.517 1

0.361 0.123

0.356 0.123

−0.175

Significance (bilateral)

1

0.361

Stability −0.175

Intelligence −0.173

Pearson correlation

−0.173

1

Gregariousness

Pearson correlation

Significance (bilateral)

Pearson correlation

Excitability

0.257

0.183

0.260 −0.250

0.204

−0.213

0.900

0.024

0.873

−0.031

0.909

0.022

0.491

0.131

0.000

0.646**

0.655

0.085

1

0.000

0.641**

0.075

0.330

0.957

0.010

0.331

0.184

−0.214

−0.239

0.824

0.042

0.798

0.049

0.327

−0.185

0.863

−0.033

0.037

0.382*

0.822

0.043

0.000

0.641**

1

0.396

0.161

0.779

0.053

0.847

0.037

Aggressiveness

Daring

0.069

0.337

0.002

−0.538**

0.886

0.027

0.572

One

0.000

0.109

−0.299

0.675

−0.080

0.518

0.591 −0.123

0.029

−0.102

0.305

−0.194

1

0.002

0.544**

0.000

0.646**

0.037

0.382*

0.009

0.466**

0.581

0.1005

0.792

0.050

−0.108

−0.400*

0.002

−0.553**

0.002

0.544**

1

0.655

0.085

0.822

0.043

0.002

0.538**

0.696

0.074

0.105

−0.302

Perseverance

Table 3 Correlation analysis table of 16 Personality Factors and speed skill performance of the tested personnel Susceptibility

Suspicion

0.608

−0.098

0.005

0.498**

0.967

0.008

0.035

0.387*

0.522

0.122

1

0.305

(continued)

0.118

−0.291

0.142

0.274

0.627

0.092

0.331

0.184

1

0.522

0.122

0.591

0.029 −0.102

−0.194

−0.400*

0.909

0.022

0.327

0.002

−0.553**

0.491

0.131

0.863

0.039 −0.185

0.010

−0.380*

0.413

−0.155

0.709

−0.071

−0.033

−0.464**

0.653

−0.086

0.036

0.384*

Research on the Relationship Between Personality… 127

Suspicion

Susceptibility

Daring

Excitability

Excitability

Aggressiveness

Stability

Intelligence

Gregariousness

Average score

Tension

Self-discipline

Independence

0.184

0.035

Significance (bilateral)

Pearson correlation

0.387* 0.092

0.967

0.008

0.675

0.518

Significance (bilateral)

Pearson correlation

0.886 −0.080

0.572

−0.123

Significance (bilateral)

Pearson correlation

0.900 0.027

0.873

−0.108

Significance (bilateral)

Pearson correlation

0.824 0.024

0.798

−0.031

Significance (bilateral)

0.042

0.200

Pearson correlation

0.049

0.190

Significance (bilateral)

Pearson correlation

0.377 0.241

Significance (bilateral)

0.611

−0.167

−0.097

Pearson correlation

−0.246

0.862

0.540

Pearson correlation

−0.033

−0.116

Pearson correlation

Significance (bilateral)

0.942 Privateness

0.383

Significance (bilateral)

0.014

0.854

Fantasy

0.165

0.786

Significance (bilateral)

Pearson correlation

0.668 −0.035

0.468

−0.052

Significance (bilateral)

Pearson correlation

0.187 0.082

0.174

Significance (bilateral)

−0.138

−0.255

Pearson correlation

Intelligence 0.248

Gregariousness

Pearson correlation

Table 3 (continued) Stability

Aggressiveness

0.771

0.274

0.005

0.498**

0.109

−0.299

0.002

−0.538**

0.260

−0.213

0.204

Excitability

Perseverance

0.634

0.195 −0.254

0.608 −0.291

0.290 −0.244

One

−0.200

0.112

0.296

0.000

−0.620**

0.035

−0.385*

0.995

0.001

0.187

0.248

0.174

−0.255

Daring

0.937

0.015

0.158

−0.264

0.006

0.488**

0.290

−0.200

−0.390*

0.020

−0.423*

0.006

0.488**

0.000

0.793**

0.185

0.249

0.324

0.186

0.000

0.654**

0.668

0.082

0.468

−0.138

Self-discipline

−0.090

0.060

−0.348

0.000

0.793**

0.112

0.296

Independence

0.489

0.131

0.106

−0.301

0.185

0.249

0.000

−0.620**

−0.098

0.000

0.069

0.337

0.183

−0.250

0.257

0.494 −0.214

0.000

0.130

0.434

0.148

0.213

0.234

Experimentation

−0.239

−0.720**

0.514

−0.124

0.047

0.366*

Anxiety

0.672

0.434 0.055

0.003

−0.148

0.324

0.186

0.035

−0.385*

−0.080

−0.517**

0.000

0.654**

0.995

0.001 0.195

0.434 0.106

0.364*

0.158

0.264

0.158

−0.264

0.060

−0.348

0.033

0.275

−0.206

0.048

0.364*

(continued)

−0.206

0.082

0.323

0.937

0.015

0.634

−0.090

0.489

0.131

0.771

0.672 0.055

0.003

−0.301

0.175 −0.390*

−0.080

0.942

0.014

0.383

0.165

−0.148

−0.517**

0.854

−0.035

0.786

−0.052

Tension

0.082

0.323

0.158

0.264

0.020

−0.423*

Suspicion −0.254

Average score

Susceptibility −0.244

128 N. Men et al.

Pearson correlation

0.099

0.603

Significance (bilateral)

0.350

Significance (bilateral)

Pearson correlation

0.177

0.312

0.216

0.001 0.233

0.053 −0.191

0.000 0.583**

0.102

−0.618**

0.660

0.084

0.974

−0.006

1

0.480

0.356

−0.175

0.988

0.003

0.037

0.382*

0.002

0.550**

1

0.974

−0.006

0.908

0.022

−0.134

0.248

−0.218

0.613

0.096

0.247

0.218

1

0.002

0.550**

0.660

0.084

0.619

−0.095

0.392

−0.162

0.756

−0.059

Independence 0.175

Experimentation 0.118

0.595

0.101

0.142

Anxiety

−0.356

0.968

Significance (bilateral)

Pearson correlation

0.619 0.305

0.392

−0.008

Significance (bilateral)

Pearson correlation

0.908 −0.095

0.756

−0.162

Significance (bilateral)

Pearson correlation

0.480 0.022

0.595

−0.059

Significance (bilateral)

−0.134

1

0.099

0.307

0.627

Privateness

Pearson correlation

0.101

0.099

Significance (bilateral)

Pearson correlation

0.307

1

Pearson correlation

Significance (bilateral)

0.331

Fantasy

*Significant correlation was found at 0.05 level (bilateral).* *There was a significant correlation at the level of 0.01 (bilateral)

Average score

Tension

Self-discipline

Independence

Experimentation

Anxiety

Privateness

Fantasy

Significance (bilateral)

Table 3 (continued) Self-discipline

Tension

0.194 0.304

0.216

1

0.000

−0.664**

0.613

0.096

0.988

0.003

0.001

0.583**

0.053

−0.356

0.350

0.177

0.048

−0.233

0.000

−0.664**

1

0.247

0.218

0.037

0.382*

0.000

−0.618**

0.102

0.305

0.968

−0.008

0.033

Average score

1

0.304

0.194

0.216

−0.233

0.248

−0.218

0.356

−0.175

0.216

0.233

0.312

−0.191

0.603

0.099

0.275

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Table 4 Indicators of character quality Item

Index

Score presentation

Features

Character traits

Susceptibility

Pearson value the higher the correlation, the stronger the correlation

Reasonable, realistic, and self-reliant

4 Conclusion Through the experiment of speed skill training results, this paper carries out psychological quality research among 30 cadets in military academies, provides a method for the establishment of psychological indicators, makes the quantification of indicators possible to a certain extent, and provides new ideas and methods for the implementation of teaching in military academies. Through the analysis of the experimental data, it can be seen that the sensitivity of cadets’ personality is related to the results of speed skill training. The more sensitive the cadets are, the better their performance in speed skill training will be. When conducting physical training and targeted training, military academy teachers should consider the influence of psychological factors on the training effect and consciously educate students to develop rational, realistic, and self-reliant personality in life [6]. In training excellent speed and skill students, we should attach importance to and give full play to the personality characteristics of people, and improve the training effect. Through the research on the psychological factors of the trainees participating in speed skill training, to a certain extent, the sensitive indicators of the psychological factors of the cadets are quantified. The special requirements of speed skill training are put forward, and the psychological indicators for physical training are provided. At the same time, due to the limitation of author’s research ability and experimental equipment, there will be some shortcomings in the speed skill training and psychological indicators, and the factors considered are not comprehensive enough. In the future, with the further development of the research, more scientific and reasonable psychological indicators will be put forward according to different physical training standards so that the psychological indicators of cadets in military academies will be more extensive. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhengzhou Campus, CPLA Army Artillery and Air Defence Forces Academy. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Zhibing P (2000) Air defense soldier man-machine-environment system engineering. Air Defense Academy, Beijing 2. Institute of Psychology, Chinese Academy of Sciences (1993) Revision of the handbook of 16 personality factor scales. Institute of Psychology, Chinese Academy of Sciences, Beijing 3. Luo F (2011) SPSS data statistics and analysis. Tsinghua University Press, Beijing 4. Tao L, Zhibing P (2011) Physiological and psychological qualities that multi-person single-machine operators should possess. Papers of the eleventh man-machine-environment systems engineering congress 5. Lu P, Li K, Zhao C (2016) Analysis and Modeling of back muscle strength and fatigue perception during back walking. Technol Innov Manag 37(7):619–624 6. Shimei WJ (2015) Job stress, self-efficacy and job satisfaction: a psychological study based on student managers of mining universities. J Xi’an Univ Sci Technol 35(5):670–674

Research on Connection Between Physiological Index and Endurance Training on Military Academy Cadets Pengdong Zhang, Zhenyou Zhang, Xuechen Yao and Zhibing Pang

Abstract Purpose is to research on the connection between physiological index and endurance training on military academy cadets. Methodology is to choose 30 cadets randomly in a military academy for tests on their physiological index and to run analysis on relativity between physiological index tests result and endurance training result with SPSS 20.2 pearson analysis tool. Results step test result had a relatively significant impact on endurance training. Conclusions in endurance training, military academy cadets should make their training well targeted according to their own physiological index, to enhance their training effectiveness. Keywords Physiological index


Endurance training
Relativity research

1 Introduction This paper applied Man–Machine–Environment System Engineering theory [1] and conducted physiological index tests on 30 cadets in a military academy, including such indexes as length, weight, lung capacity, step test index, oxygen saturation, and perfusion index (pi). Meanwhile, their endurance training result (four times) was obtained. With analysis on the physiological index and endurance training result, the connection between the physiological index and endurance training result was figured out and provided recommendations to supported military academy instructors in well-targeted training.

P. Zhang
Z. Zhang
X. Yao (&)
Z. Pang Zhengzhou Campus, CPLA, Army Artillery and Air Defence Forces Academy, Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_15

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2 Subjects and Methodologies 2.1

Subjects

Choose 30 cadets from a military academy randomly (No.1–30), all male, aged 22– 27, normal blood pressure and pulse, and in good physical condition.

2.2 2.2.1

Methodologies Measuring Instruments

Five EW3002 electronic sphygmomanometers, to measure heart rate of the subjects during training and test; one EMOVC-101II electronic spirometer, to measure lung capacity of subjects; one HN-283 electronic weight scale, to measure the weight of the subjects; five stopwatches for timekeeping; a band tape to measure length of the subjects; one Masimo pulse oximetry; one TZCS-1 step tester.

2.2.2

Physiological Index Tests

Length: the subject stands to the wall, keeping legs together and shoulders relaxed, to measure the length between heals and top. Weight: the subject in short-sleeved shirts and shorts, bare boot, standing upright on the electronic scale to measure the weight. Lung capacity: the subject breathes to the end, and then breathes out fully to the spirometer. To measure twice, take the maximum value. Step test index: the step was 30 cm in height, with a metronome vibrating 120 times per minute. The subject stands before the step, climbing up and down the step according to the metronome vibration. Repeat the action for three min and then sit down on a chair, to measure the pulse for three times: 1–1.5 min after test, 2– 2.5 min after test, and 3–3.5 min after the test. Step test index reflects the functionalities of the cardiovascular system: higher step test index indicates better functionality of the cardiovascular system, and vice versa. Oxygen saturation: it means the blood oxygen level. As an important physiological index of the breathing cycle, the normal value of oxygen saturation is 90%. Perfusion index (PI): PI reflects the pulsing blood flow. Higher blood flow in pulsing indicates a stronger pulse, and the PI will be higher.

Research on Connection Between Physiological …

2.2.3

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Endurance Training Tests

Endurance test is conducted on 30 cadets for four times every other week. This test was included in daily training and final examination of cadets; the test standard had been clearly defined and the test was rigorously conducted; the subjects were familiar with the procedure and were mentally relaxed. Hence, the test result was representative. The average value of the four tests was taken as the final result of endurance training test.

2.3

Statistical Data Processing

Using data analysis tool in SPSS 20.0 program conduct relativity analysis between six physiological indexes and average endurance training result of the 30 subjects [2].

3 Statistics and Analysis for Data The physiological index test results of the subjects, see Table 1. Endurance training result of the subjects, see Table 2. Conduct relativity analysis between physiological index tests result and endurance training result with SPSS 20.2 pearson analysis tool [3, 4], the result, see Table 3. Table 1 Physiological index test results No.

Length

Weight

Lung capacity

Step test index

Pulse

Oxygen saturation

Perfusion index (PI)

1 2 3 4 5 6 7 8 9 10 11 12 13

173 173 173 167 182 183 171 172 174 169 184 173 168

62 76 66.7 60.5 69.8 81.9 62.1 65.3 6436 66.9 77.4 67.2 61.7

4212 5124 3705 3877 4619 5694 3790 4251 4335 4040 4470 4525 4159

71 57 63 81 66 53 63 73 75 94 63 51 61

74 75 73 88 68 84 77 65 58 82 73 86 82

100 99 97 98 100 98 99 98 99 99 100 99 99

2.6 7 8.8 6.4 2.3 6.3 5.1 7.6 4.7 6.5 3.1 4.6 3.9 (continued)

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Table 1 (continued) No.

Length

Weight

Lung capacity

Step test index

Pulse

Oxygen saturation

Perfusion index (PI)

14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

174 179 178 175 185 172 180 183 179 179 181 173 175 184 182 178 179

68 70.8 79 80 76 67.2 65.7 65 78.3 78.8 72.9 70.1 68.6 76 82 69.1 80

3623 4288 3655 3758 4778 3967 5175 4131 4436 4202 3610 4494 5148 4974 4602 5934 4415

45 59 78 68 74 47 83 66 80 68 56 48 68 63 76 76 72

76 81 66 78 74 100 56 65 67 74 98 91 59 56 62 60 71

99 98 99 98 99 100 99 97 100 100 99 98 100 100 99 99 100

2.9 6.6 9.6 6.4 3.1 2.8 3.6 1.6 1.6 3.6 1.1 1.1 1.7 1.7 1.1 2.9 2.1

Table 2 Endurance training result No.

Result 1

Result 2

Result 3

Result 4

Average

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

21.06 23.36 21.32 20.03 21.52 22.46 22.58 21.08 21.53 22.39 21.59 24.02 21.45 21.06 22.15 21.39 21.50 22.34

22.07 20.49 21.31 20.14 20.16 23.46 22.52 21.19 21.41 21.23 21.52 24.20 21.22 21.15 21.20 21.30 22.02 22.35

19.44 21.43 20.56 20.06 19.10 22.39 22.39 21.20 21.09 21.34 21.32 21.39 21.08 20.36 22.02 21.23 22.06 22.19

21.21 21.43 21.13 20.40 20.21 22.53 22.33 21.41 21.10 21.33 21.31 21.57 21.11 21.13 21.19 21.25 22.46 21.28

20.95 21.68 21.08 20.16 20.25 22.71 22.46 21.22 21.28 21.57 21.44 22.80 21.22 20.93 21.64 21.29 22.01 22.04 (continued)

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Table 2 (continued) No.

Result 1

Result 2

Result 3

Result 4

Average

19 20 21 22 23 24 25 26 27 28 29 30

22.13 22.12 21.25 21.06 22.07 21.52 22.47 21.05 21.36 21.34 21.08 21.27

22.36 20.16 22.04 20.16 22.11 21.34 20.42 22.11 22.06 21.24 21.54 22.12

22.05 19.59 21.19 19.39 21.24 21.09 21.38 21.01 21.26 21.13 19.46 21.52

22.28 20.05 21.06 23.17 21.30 21.18 21.58 20.58 20.42 21.34 19.37 21.33

22.21 20.48 21.39 20.95 21.68 21.28 21.46 21.19 21.28 21.26 20.36 21.56

Table 3 Relativity analysis between physiological index tests result and endurance training result of the subjects

Average result

Length

Weight

Lung capacity

Step test index

Pulse

Oxygen saturation

Perfusion index (PI)

Pearson relativity

0.023

−0.031

−0.041

−0.432*

0.412*

−0.075

0.168

Significance (two-sided)

0.905

0.873

0.831

0.017

0.024

0.693

0.375

*Significant relevant to 0.05 level (two-sided) **Significant relevant to 0.01 level (two-sided)

With analysis of Table 3, conclude among all physiological indexes of the subject, step test index and static pulse were significant relevant to endurance training result.

4 Conclusion The experiment result indicated that among all physiological indexes of the subject, step test index and pulse were significant relevant to endurance training result. Higher step test index reflects better functionality of the cardiovascular system, and vice versa. Cadets with a higher step test index achieved better endurance training result [5]. In physical fitness training, instructors in the military academy should conduct targeted training consciously, to improve the training effectiveness. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhengzhou Campus, CPLA Army Artillery and Air Defence Forces

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Academy. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Zhibing PANG (2000) Air defense forces man machine environment system engineering. Air Def Forces Acad, Zhengzhou 2. Fang LUO (2011) SPSS data statistics and analysis. Tsinghua University Press, Beijing 3. Qin L, Pang Z (2010) Physiological and psychological quality for operators in one-operatorone-machine operating. In: Proceedings of the 10th international conference on MMESE 4. Tao LI, Pang Z (2011) Physiological and psychological quality for operators in multiple-operator-one-machine operating. In: Proceedings of the 11th international conference on MMESE 5. Lu PENG, Zhao LI, Cai-j K-wei (2016) Analyses and modeling of back strength and perceived fatigue when carrying a bag and walking. Technol Innov Manag 37(7):619–624

Research on the Generation Law of Single-Machine Operation Skills Haitao Zhao, Cheng Jin, Xing Su, Genhua Qi and Zhibing Pang

Abstract In this paper, the rule of the generation of single-machine operation skill is studied through experiment, which can make the operator adapt to operating environment quickly and complete the task. Methods: Multi-group operation was carried out to explore the basic rules of skills by recording experimental data, drawing curve dynamic graph, and comparing multiple sets of data. Through the combination of theory and practice, the general rule of skill generation was obtained by analyzing the graph, and there was a certain mechanism. Results: Whether single-person or multi-person operation, its skill generation rules follow a certain pattern, but complex operations and multi-person operations are more complex. Keywords Professional skills


Generation rule
Single-machine operation

1 Introduction Skill is the ability of a person to apply knowledge and intelligence to solve practical problems. It is the necessary ability to complete an activity successfully. And skill is also acquired through practice [1]. Military skills are professional skills in military work and are the skills or abilities that military personnel must master in the conduct of military activities with the knowledge and experience they have learned to accomplish a task. Military skill is the skill that the soldier must learn, the things that the contemporary revolutionary army must be, the important part of military training, and the key content of army training. At present, military equipment is constantly being upgraded, which requires the solider master a new professional

H. Zhao
C. Jin (&)
G. Qi
Z. Pang Zhengzhou Campus, CPLA, Army Artillery and Air Defence Forces Academy, Zhengzhou 450052, China e-mail: [email protected] X. Su Troop 32151, Huining Town, Xingtai 054000, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_16

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skill fast. At the same time, not only to their own rapid grasp, when as a teacher, but also to learn effective organizational training, so that the beginners can master professional skill quickly.

2 Process of Skill Generation The process of forming skills can be divided into six stages and has its own rules. In the whole process of skill generation, if we master the characteristics of each stage and formulate specific means and methods according to its characteristics, the cycle of skill generation will be shortened, the formation of skills will be accelerated, and good and fast results will be achieved [2, 3].

2.1

Initial Stage

The initial stage is the beginning stage of skill generation, the first leap in the process of skill learning, and the main skill base reserve period. There was a marked increase in skills at this stage [4]. The reasons mainly depend on the following factors: thirst for knowledge of the learner, psychological, and physiological state, the quality of coach, training methods, equipment support conditions, and natural environment, etc.

2.2

Formative Stage

The formative stage is the second stage of skill generation and the first transition period in the process of skill generation. It is positive and is an important skill dynamic shaping preparation stage. The rate of skill growth decreases significantly. At this stage, the improvement rate of skills is also slow. It is because of the end of the learner’s imitation in the initial period, whose proficiency has been initially stereotyped.

2.3

Platform Stage

The platform stage is the third stage of skill generation, which is the first stable period in the process of skill generation. And it is the temporary stabilization stage of lower level. After the formative stage, the operator’s skill level appears to hover

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repeatedly and seems to reach a stable saturation. But this is only temporary stability and is the skill stable saturation of the false phenomenon. At this stage, the skill level is in a state of relatively stable and does not rise (or rises very slowly).

2.4

Plateau Stage

The Plateau period is the fourth stage and is the second transition period in the process of skill generation. It is negative and is a difficult period. There are three distinct features of this phase: One is that it takes a lot of time to practice and has little efficiency, the other is that skills fluctuate significantly and the stability is poor, and third, there is a clear downward trend in skills [5].

2.5

Breakthrough Stage

The breakthrough stage is the fifth stage and is the second leap in the process of skills’ generation. It is the sublimation and leap stage of skills from perceptual knowledge to rational knowledge and from rational knowledge to practice. It is the qualitative leap stage of skill generation and the leap stage of proficiency and skills’ formation. The remarkable feature of this stage is the very high efficiency of skill generation, the qualitative leap of skill quality, and the breakthrough in time, precision, and the sensitivity and dexterity of action.

2.6

Stable Stage

The stable period is the last stage, the second stable period in the process of skill generation, and the stage when the skills are really stable. This stage has three obvious characteristics: first, the skill is relatively stable, and the achievement does not appear which greatly fluctuates. Second, the psychological quality of learners is relatively high stability. After the previous stages, the impact of psychological quality by a variety of natural environment and human factors is little, and the psychological stability is at high degree. Third, the skill level has reached the automation. In the process of operation, learners’ visual operation and conscious control have been reduced to a minimum, and their skills show a high success rate.

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3 Experiment Research In order to verify the law of skill generation, we carry out an experiment, combining with the relevant teaching activities. In the experiment, we collected the data of equipment operation and provided data support for the research of skill generation rules.

3.1

Experiment Subject

The subjects were 21 male students, aged 22–25, with an average age of 23.3 years. The height is in 160–185 cm, with average height of 171.5 cm. The weight is in 60.4–85.3 kg, with average weight of 70.0 kg.

3.2

Experiment Equipment

The experiment is to collect the operation data of two kinds of equipment operation. Operation I is one person to operation; Operation II is three persons to operate together.

3.3

Experiment Site

The experiment site is selected on the ground with smooth surface, wide field of vision, good light, and easy to organization. Due to the need of operating equipment, the soil of the site is a little soft.

3.4

Experiment Process

First of all, each person to do the Operation I. In the process, it is to record the operation results. Then, according to the performance level of everyone, we divide the 21 persons into 7 trios. We strive to make no significant difference between the different trios of Operation I. The 7 trios are doing Operation II following. Assessment criteria. In order to simplify the assessment criteria, we use the time of equipment operation of setup and roll-up to measure the level of operation. When an error occurs during the operation, the operator re-performs the corresponding steps immediately, the repeating time is adding up, and the final result is the time after the accumulation.

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Table 1 Meteorological environment of the experiment First day Second day Third day Fourth day Fifth day Sixth day

Weather

Temperature (°C)

Wind speed (m/s)

Sunny Sunny Sunny Cloudy Cloudy Sunny

13–20 13–22 15–20 12–19 13–22 15–26

2.20–4.56 1.77–4.25 0.88–2.41 4.60–6.01 6.72–10.22 1.91–4.19

The training and examine of Operation I and Operation II were carried out in 5 days. It is to examine at the same time as the exercise and record the results. Operation I was done in the first two days, and according to four half-day order, each half-year examine 2, 3, 4, 3 times. Operation II was done in the following three days, according to six half-day order, each half-day assessment 1, 1, 2, 2, 2, 2 times. In the process of the experiment, the outdoor meteorological environment is tested, and the test instrument is as: KestrelNK4500. The measured values are shown in Table 1.

4 Experimental Data and Analysis 4.1

Operation I Performance

Operation I is a single-person operation, and the operation time of each examine is shown in Table 2:

Table 2 Each operation time of Operation I Setup Roll-up

1

2

3

4

5

6

7

8

9

10

11

12

112 85

102 78

86 74

78 67

81 66

90 63

87 58

78 79

75 58

75 53

75 51

78 50

Fig. 1 Operation time of Operation I change curve (smaller and better)

150 100 50 0

1

2

3

4

5

Sey-up

6

7

8

9 10 11 12 Roll-up

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According to Table 2, its change curve is shown in Fig. 1. Figure 1, it is that with the increase of operation times, the operation time presents a downward trend.

4.2

Operation II Performance

Operation II is three-person operation. The operation time of each assessment is shown in Table 3. According to Table 3, its change curve is shown in Fig. 2.

4.3

Data Analysis and Discussion

According to Figs. 1 and 2, it can be concluded that whether single or multi-person operation, its setup and roll-up time, the overall will show a decreasing trend. However, in the process, the performance of operation will be repeated, which is consistent with the performance of various “transition periods” in the process of skill generation. The overall trend is consistent with the rule of professional skill generation. This further indicates that the more the number of operations, the degree of proficiency will be higher and more skilled in the mastery of skills. Thus, it is further explained that the process of generating professional skills is from initial learning to basic mastery to steady improvement and finally to complete proficiency and automation of professional skills. At the same time, we calculate the standard deviation coefficient (Vr ) of I I I ¼ 0:132752, Vrrollup ¼ 0:169818,Vrsetup ¼ 0:268791, Operations I and II. Vrsetup II Vrrollup ¼ 0:273549. That is, the performance dispersion of multi-person operation is

Table 3 Each operation time of Operation II Setup roll-up

1

2

3

4

5

6

7

8

9

10

328 240

301 174

292 157

248 192

271 130

215 143

189 124

152 113

158 100

160 117

Fig. 2 Operation time of Operation II change curve (smaller and better)

400 300 200 100 0

1

2

3

4 Set-up

5

6

7

8

Roll-up

9

10

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greater than the one-person operation. This shows that the performance of Operation II has a larger range.

5 Result Through the experiment of single-person operation and multiplayer operation, the rule of skill generation based on the action is verified. On the whole, the rule of skill generation is consistent with the general rule for both single-person operation and multi-operation. According to the different characteristics of each stage, coaches should obey the basic rules, conduct scientific and effective organization, carry out theory and practice teaching, and guide learning operators to improve their skills on the basis of standard, safety, and accuracy, so as to achieve comprehensive improvement. Through the experiment, it is found that we should focus on reasonable planning from the following aspects: First, in the “initial period” to lay the foundation, so that it forms a correct, standardized operation action. It will be good for reducing the occurrence of invalid actions during the later practice. Second, in the whole process of practice, the coach should pay attention to psychological regulation and reduce the impact of psychological fluctuations on the operation. In the latter part of the practice process, the opportunity to improve the skill level is often closely related to the individual psychological conditions. Only when the psychological condition is stable, the skill level can continue to improve. In other words, the later skill practice is mainly the process of improving the psychological quality in the homework. Third, when do the multi-person operation, team cooperation is extremely important. In the experiment, the results of Operation II were more discrete than Operation I. On the one hand, Operation II is relatively complex than Operation I, and on the other hand, there is a high probability of error in Operation II. The error has the influence to the achievement is larger, this is reflected in the achievement standard deviation coefficient is larger. With the deepening of the practice, there is more tacit cooperation between multi-persons, so that the final score has a greater change than the initial score.

6 Conclusion The purpose of studying the rule of skill generation is to improve efficiency, shorten time, and find suitable methods in the whole process of skill generation, so as to achieve the stability and reliability of skills. Moreover, according to the

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characteristics of each stage, adjust the learning method, can enhance the enthusiasm of learners, more and more confidence in the operation, improve the interest of learners, and ultimately make the skills teaching process to achieve a safe, economical and efficient purpose. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Zhengzhou Campus, CPLA Army Artillery and Air Defence Forces Academy. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Pang Z (1999) Military skill science. Air Defense College, Zhengzhou 2. Lu K (1987) Creative psychology and techniques. Northwestern Polytechnical University, Xi’an 3. Zhao T (2016) Exploration and research on the formation law of military skills. Guid Sci 29:186 4. Pang Z, Liu J, Jin C et al (2013) Grasping the “3-Nature” in the teaching of strengthening training of professional skills. Educ Res Inf Air Def Acad 5. Pang Z, Yin Q, Ou H (2012) Study on influence of stamina to the performance of one person operating one machine and one person operating multiple machine. Proc 12th Conf Man-Mach-Environ Syst Eng 10:35–39

Eye Gaze Orientation and Pupil Size Variation on Time-Series Vigilance Task Deqian Zhang, Wenjiao Cheng and Hezhi Yang

Abstract Monitoring work performance declined has became need solution of important problem, and eye gaze orientation and pupil size related Monitoring task performance also worth to explore, to prevent the security monitoring personnel’s fatigue and performance decline. This research in simulating monitoring task based on Machworth’s Clock Test use the eye tracker to measure the attention direction and pupil size of the subject, and subjective evaluation of fatigue and attention. The results show monitoring work performance declined with the time-series on. Pupil size relates to fatigue and eye gaze orientation relates attention. It is discussed to evaluate the attention by controlling eye gaze orientation and fatigue to enhance monitoring performances.







Keywords Vigilance performance Hit ratios Reaction time Attention Eye gaze orientation Pupil size Monitor











Fatigue


1 Introduction Monitoring work performance declined has became need solution of important problem, and eye gaze orientation [1] and pupil size [2] related Monitoring task performance also worth to explore, to prevent the security monitoring personnel’s fatigue [3] and performance decline. This research in simulating monitoring task based on Machworth’s Clock Test uses the eye tracker to measure the attention direction and pupil size of the subject, and subjective evaluation of fatigue and attention [4].

D. Zhang (&)
W. Cheng
H. Yang Psychology Department, Jinggangshan University, Jian 343009, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_17

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2 Methods 2.1

Participants

The experiment is implemented by eight healthy subjects, undergraduate students, right-handedness, three males, and five females. The average age is 23, ranged from 17 to 25 years. All participants report their visions are normal or corrected to normal, and they do not have any problems of nervous system. They are not trained before, and signed the informed consent which meets Chinese ethical norms before the experiment.

2.2

Material and Designs

The vigilance mission aims to let the participant monitor the movement of the second hand by simulated Mackworth’s [5] clock test on radar task, based on the theory of signal detection. The second hand moves clockwise for one space each second. When finding the second hand move two spaces once, it is as the signal, the participant is required to click the left button of the mouse immediately. Meanwhile, the software records the data and generates a new random sequence signal (between 8 to 52 s) automatically [6]. The experiment lasts for 80 min. The participants are required to keep watching the movement of the second hand. The computer program automatically follows and records the hit reaction, reaction time, detection leakage, and false alarm [7]. Eye tracker measures and records the attention direction and pupil size of the subject. After the experiment, the participants are required to write inventory that includes fatigue and attention [7].

2.3

Data Analysis

The MATLAB 7.8 software is used for statistic and data analysis.

3 Results 3.1

Eye Gaze Orientation to Screen

In 80 min monitoring operation process, there is a clear drop of monitoring performance (hit ratios)-related eye gaze orientation at the 500–1000th, and the 3000– 4000th seconds that we found that the monitor’s attention direction is off the screen’s monitoring target as shown in Figs. 1, 2, and 3.

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Gaze Orientation to Screen for Timeseries

Vertical/px

500

0 -500 -1000 0 1000

1000 2000

Timeseries/s

500 3000

0

4000 5000

Horizontal/px

-500

Fig. 1 Three-dimensional map of eye gaze orientations (vertical screen and horizontal screen) on monitoring task for 80 min (4800 s) (display resolution 1024*768 px) 400

Gaze Orientation to Screen for Timeseries

200

Vertical/px

0

-200

-400

-600

-800 -1000 -500

0

Horizontal/px

500

1000

Fig. 2 Eye gaze orientations (vertical screen and horizontal screen) on monitoring task for 80 min (4800 s) (display resolution 1024*768 px)

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Gaze Orientation to Screen for Timeseries

400

200

Vertical/px

0

-200

-400

-600

-800

-1000

0

1000

2000

3000

4000

5000

Timeseries/s Fig. 3 Eye gaze orientation (vertical screen and time-series) on monitoring task for 80 min (4800 s) (display resolution 1024*768 px)

Figure 1, three-dimensional map shows that the monitor’s attention has deviated from the target and the data we collected show that the distribution of data points is uneven during the monitoring process, which indicates that the monitor’s line of sight deviates from the attention target and it will reduce the monitoring performance. Figure 2 shows that we find that the monitor’s gaze in the monitoring process is around the analog clock for circular operation. The distribution of the scatter plot is ring-shaped, indicating that the monitor’s line of sight is tracking target and attention is concentrated. And a small amount of scatter is distributed outside the ring. It may be that the monitor does not pay attention to the target. And even there are very few scatter points distributed outside the screen area, indicating that the attention shifts or does not pay attention to the target. The latter will result in a monitoring operation error. Figure 3 shows that in the 4800 s time-series process of the monitoring work, the density of the scatter distribution indicates that it is the frequency of the monitor screen we collected, which is related to the monitoring performance, and the greater the scatter density, the better the monitoring performance, and the smaller the

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scatter density, the worse the monitoring performance. And found that in the vertical direction of the screen, a few scattered points deviated from the screen to the bottom. This is a sign that monitors are paying attention to deviations and monitoring performance degradation.

3.2

Pupil Size

Figure 4 Shows that the monitor’s eye pupil size changing course on the operation process at 4800 s. The eye pupil size reflects the operator’s fatigue and attention states. The diameter of the pupil is between 1.5 and 3.5 mm, which is beneficial for attention and monitoring. When the pupil diameter is less than 1.5 mm, the operator’s eyes are in a state of fatigue or drowsiness, which is not conducive to monitoring work, which may result in decreased performance or may cause operational errors. Pupil Diameter for Timeseries

5

Left Right

4.5 4

Pupil Diameter/mm

3.5 3 2.5 2 1.5 1 0.5 0

0

1000

2000

3000

Timeseries/s Fig. 4 Pupil size (diameter) on monitoring task for 80 min (4800 s)

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Figure 4 is a typical example of an operator. The pupil is very small at the 500– 1000th second. We learned through conversation and observation that the operator is a sleepy episode and the left and right eyes interact, as shown in Fig. 4, the time phase is based on right eye work.

4 Discussion and Conclusions In the study, we also find that the monitoring decrease in time-series monitoring task, and find that the performance drop is affected by attention concentration and fatigue. Pupil size is associated with attention and fatigue and is also related to monitoring performance. The direction of the eye’s gaze can reflect the monitor’s attention. The use of eye movement gaze orientation and pupil size indicators can be used to assess the monitor’s attention and fatigue status, which has specific implications for monitoring performance management. Acknowledgements We thank the students and control subjects for their participation. The skillful work by monitoring expert Mr. Deqian Zhang is gratefully acknowledged. This study is financed from the National Natural Science Foundation of China (No. 31260238), the regional agreement on psycho-training and clinical research in Jinggangshan University, Jian City project. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Jinggangshan University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Montague E et al (2011) Modeling eye gaze patterns in clinician-patient interaction with lag sequential analysis. Hum Factors 53(5):502–516 2. Thackray RI, Touchstone RM, Bailey JP (1978) Comparison of the vigilance performance of men and women using a simulated radar task. Aviat Space Environ Med 49(10):1215–1218 3. Ramirez-Moreno JM et al (2019) Health-related quality of life and fatigue after transient ischemic attack and minor stroke. J Stroke Cerebrovasc Dis 28(2):276–284 4. Geden M, Staicu AM, Feng J (2018) Reduced target facilitation and increased distractor suppression during mind wandering. Exp Psychol 65(6):345–352 5. Zhang, DQ, Chen WJ, Yang HZ (2017) Attention state related EEG spectrum and pupil size in vigilance task. In: The 2nd international conference on mechanical control and automation (ICMCA 2017), ISBN: 978-1-60595-460-8: 231–240 6. Zhang D, Cheng W, Yang H (2018) Predict the performance of visual surveillance by EEG spectral band advantage activity: modeling-based occipital alpha waves advantage activity. In: Long S, Dhillon B (eds) Man–machine–environment system engineering. MMESE 2017. Lecture Notes in Electrical Engineering, vol 456. Springer, Singapore 7. Zhang D, Cheng W, Yang H (2019) Evaluation of workload, arousal, fatigue, and attention on time-series vigilance task. In: Long S, Dhillon B (eds) Man-machine-environment system engineering. MMESE 2018. Lecture Notes in Electrical Engineering, vol 527. Springer, Singapore, pp 65–69

Research on Psychological Management of Officers and Men in MOOTW Zaochen Liu, Peng Gong, Yunqiang Xiang, Doudou Shan and Ailing Cheng

Abstract The final foothold towards management activities is psychological management on human. From the past course of action in conducting MOOTW tasks, the psychology of officers and men were subjected to severe test, so we need urgently improve scientific understanding on psychological management and further develop the function of management from the angle of psychology, thereby we can guarantee officers and men to have stable psychological state and to keep the lasting fighting capability. On the basis of the present psychological healthy state of officers and men and analysis of psychological capability demand, the essay discusses the path by which effectively psychological management of officers and men are realized from the five functions of management, and this will play certain theoretical and guiding significance on improving scientificity and effectiveness of troops’ management. Keywords MOOTW


Psychological management

In recent years, the frequency, intensity and difficulties in which troops conduct MOOTW are becoming larger and larger, new requirements are put forward towards troops’ management, in particular towards psychological management of officers and men. From the past course of MOOTW nervousness, complexity, cruelty and hardship will lead to huge influence on psychologically cognitive ability, emotional control ability, physiological and psychological tolerance and patience ability and confronting psychological stress ability. Their physiological and psychological function is changing, so all these influence generation and improvement of the fighting ability. So we need forcefully attach importance to their psychological health, understand their psychological characteristics and promote scientific understanding towards psychological management. From the angle of psychology, we further develop the function of management, thus guarantee officers and men to have stable psychological state and keep the lasting fighting capability. Z. Liu
P. Gong (&)
Y. Xiang
D. Shan
A. Cheng Artillery and Air Defense Forces Academy (Zhengzhou Campus), Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_18

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1 Psychological Healthy State and Psychological Ability Demand of Officers and Men in MOOTW Prerequisite of psychological management is the accurate analysis towards psychological healthy state and the accurate understanding towards psychological ability demand [1].

1.1

The Real Psychological Healthy State of Officers and Men in MOOTW

As a kind of lasting psychological state with high efficiency and personal satisfaction psychological health plays an important health care and promoting effect towards officers and men. Firstly, their psychological cognitive ability is disturbed. On the one hand, MOOTW is very political and sensitive. Once officers and men are influenced by law, regulations and policies or by local religions and customs in the mission area it will be much easier for them to make cognitive confusion. On the other hand, it is much easier for them to lead to cognitive error because of information factors. Secondly, emotional reaction of their stimulation is very changeable. MOOTW is generally conducted in the poor geographic environments under the extremely worse climate condition where their emotional ups and downs will be greatly rising; even they lose their emotional control; Much more difficult logistic supply and support, and unfixed accommodation and shelter can make them have extraordinary physiological and psychological burden and produce some unhealthy emotion such as sadness, anxiety, depression, excessive sensitiveness and solitary. Thirdly, their psychological endurance encounters challenge. All the time officers and men are forced intense psychological stress state, much heavier mental load, much higher tension of their organism, excessive psychological self-adjustment mechanism and human limits of psychological patience during the continuous MOOTW all day and all night. Fourthly, their psychological stress reaction is continuously intensified. Study on military psychology indicates that officers and men will be in psychological stress state when unexpected risk appears, and they immediately make decision and take actions towards unexpected change in military operation. When psychological stress reacts fiercely and exceeds their normal endurance limits, it will cause officers and men to produce a series of problems such as limits in self-perception and attention, slow thinking, inflexible action, much weaker adaptability of organism, being down in spirits, decreasing thinking and judging ability, loss of self-control, ineffective self-control on their own consciousness and behaviour [2].

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1.2

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Psychological Ability Demand of Officers and Men in MOOTW

Psychological ability needed by officers and men is the detailed index put forward according to each psychological quality performing mission must have. From the above-mentioned analysis of psychological healthy state officers and men should have the following psychological ability. One is that they need much stronger cognitive ability. In performing MOOTW officers and men need have much stronger cognitive ability, this mainly embodies fast familiarity towards combat environment, efficient recognition towards mass information and reasonable prediction of behavioural effect. However, combat situation is always changeable and it is much more difficult to recognize true or false information. Under the circumstance, these can often increase normal cognitive difficulties and probability of cognitive error, even lead to misconception and influence task process. The contradiction between reality and demand is the important factor which seriously influences smooth implementation of MOOTW. If we want to solve the contradiction, we forcefully need to cultivate stronger cognitive ability of officers and men. Two is that they need continuous motivation of behaviour. Their motivation of psychological development is mainly composed of demand and motivation, demand triggers motivation and in turn motivation drive individual to produce behavioural activity so as to meet demand. When their demand in much lower level are met they may seek for much advanced spiritual demand, the contradiction between new demand and initial psychological development level has become the motivation of psychological development. Psychological motivation is the most active and influential factor in psychological quality and its degree has played accelerated or released role on the development of psychological quality of officers and men. Three is that they need much stronger anti-frustration ability. When individual engages in purposeful activities, frustration here refers to a kind of nervous state and emotional reflection produced because of obstacle and disturbing from subjective or objective condition, under the situation expected motivation cannot be smoothly realized and met. The cause of frustration may generally include intrinsic and extrinsic factors. Extrinsic factors mainly derive from outside environment and cannot be influenced by personal will and ability; intrinsic factors mainly derive from personal condition and limit which hinder the realization of the targets, including personality, moral quality and psychological state [3]. In conducting MOOTW because of imperfect and immature personality and terrible extrinsic condition, it is much easier for some officers and men to produce unstably and extremely emotional reflection with frustration. So all these will require officers and men must have firm will and character, stronger anti-frustration endurance ability.

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2 The Path Where the Efficient Psychological Management Is Realized in MOOTW More and more managers have also realized the core of management focuses on psychological management. In management process, we should fully develop management function such as plan, organization, leadership, motivation and control. We adjust and control the two sides of management whenever necessary, the psychological management is not only the basis of management work usually, but also the basis of promoting and keeping the fighting ability in conducting MOOTW task.

2.1

Develop Organization Function, Realize the Efficient Systematic Management

Organization function of management is to realize effective division and cooperation through establishing, maintaining and continuously improving organization structure, the purpose is to finally realize confirmed management targets. Army is a highly centralized organization; psychological management heavily relies on military organization. So in the activities of psychological management developing organization function is to clarify sector division and allocation of rights and responsibilities. According to the above-mentioned target module of psychological management, we should importantly perform the following contents very well. One is to establish the correspondent sectors, clarify division and confirm the integration of power and responsibilities according to plan and tasks. Two is to select, train, assess and deploy staff, confirm motivation mode and methods towards staff. Three is to make subordinate relationship in different level and collaboration of different department in the same level clear so as to guarantee continuity and order. Four is to frequently adjust local problems and solve occurring or possibly occurring contradiction and conflict whenever necessary in performing tasks. A dynamic equilibrium should be maintained between the activities of psychological management and the process of performing the tasks so that effective systematic management is realized [4].

2.2

Develop Leadership Function; Realize the Efficient Position-Level Management

From the angle of management, leaders will play a crucial role on the activities of troops’ management. When any military organization implement management they need have overall plan of management activities, adjust all kinds of relation, make decisions and issue directives, in other words, we should develop organization

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function of leaders. From the angle of psychology, the role of leaders lies in establishing effective motivation, develop role model function, through their own role model leaders inspire and lead officers and men, that is, we should develop leaders’ motivation. So if we want to arrive at the targets of psychological management and realize effective hierarchical management, firstly leaders in different level should be good at control the situation, grasp the important point and in the meantime have the overall plan; secondly, they should be good at motivate the enthusiasm of officers and men, make full use of their advantages and avoid their disadvantages; thirdly, they should be good at solving contraction and cherish time, flexibly deal with all kinds of relation and improve efficiency of management activity.

2.3

Develop Motivation Function, Realize the Efficient Psychological Management

After organization and plan are confirmed, we should reinforce management effectiveness, one of the important measures is to motivate the enthusiasm of officers and men, that is, through motivation means we motivate combat desire of officers and men, excavate their own potentials and create conditions to make them develop their subjective initiative and creativity. In other words, we should develop motivation function. The starting point of motivation is the demand of officers and men; the demand is the aspiration and motivation producing engaging in certain activity, in turn motivation dominates the behaviour of officers and men. So based on the analysis of demand of officers and men, motivation is to combine management targets with personal demand, through certain methods and means the enthusiasm is aroused, motivation means generally include spiritual motivation and material motivation. In MOOTW, we mainly adopt spiritual motivation including positive motivation such as praise, meritorious performance and promotion in advance, negative motivation such as punishment. In addition, a typical example motivation mode is adopted; a typical character is set and arouses the enthusiasm of other officers and men [5]. Effect of management mainly focuses on psychological management. With the continuous innovation of management theory and gradually rich management practice as perfectness of troops’ management, psychological management has played a decisive role on improving scientific management level of troops, meeting new challenge psychology of officers and men faces and solving new problems of their psychology. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Artillery and Air Defense Forces Academy (Zhengzhou Campus). All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Yu G (2006) Social psychology. Beijing Normal University Press, Beijing, p 499 2. Wu X, Lin L (2012) Psychology in the military. Chinese Light Industry Press, Beijing 145–165 3. Tang Y (2013) On troops management in MOOTW. Grassroots Political Work, Beijing. Air force Newspaper (3), pp 28–29 4. Zhu W, Zhang B (2008) Focusing on anti-frustration education towards college students. Guangming Daily, 2008-04-14 (5) 5. Chen X (2006) An introduction of frustration education. Chinese Scientific and Technology University Press, Hefei, p 158

The Influences of Capability and Character on Human’s Manual Dexterity Shun Yao, Shengping Zhao and Zhongting Zhou

Abstract In order to investigate the impact of human’s capability and human’s character on manual dexterity, 83 college students as subjects were tested by BD-II-601 manual dexterity testing instruments. Two comprehensive evaluation parameters, namely “general athletic capability” and “artistic capability,” were constructed. Boxplots, two-factor ANOVA with repeated measures, t-test and other statistical methods were employed to analyze and test the experiment data. Statistical results show that the main effects of “general athletic capability” and “artistic capability” on the results of manual dexterity tests are statistically “very significant” (p < 0.01) and statistically “significant” (p < 0.05), respectively. However, the interaction of two comprehensive evaluation parameters is not statistically significant (p > 0.05). And, “character” should be considered as an interference factor to the results of manual dexterity tests. Keywords Safety management Statistical analysis


Safety ergonomics
Influencing factors


1 Introduction From the perspective of safety ergonomics, it is one of the several important links for human–computer interaction that a person controls the machine with his hands [1]. Once the person makes a mistake in operation, it may lead to an accident. Relevant data show: Nearly 90% of motorized equipment accidents are caused by human misoperation [2]. According to the theory of accident proneness, “those prone to accidents” tend to have dull motor nerves and make stiff and inflexible movements [3]. The above discussion leads to the concept of safety occupational aptitude, that is, the features of physical and psychological qualities that a person must possess when engaged in a certain occupation [4]. For example, manual S. Yao
S. Zhao (&)
Z. Zhou College of Safety Science and Engineering, Nanjing Tech University, Nanjing 211816, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_19

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dexterity refers to a person’s capability of quickly, accurately and harmoniously operating small objects with fingers. It is indispensable for people engaged in controlling, driving and other occupations [5]. On the problem of influencing factors of manual dexterity, researchers have carried out a number of experiments. For example, Zhao et al. [6] once analyzed the impact of two factors (“gender” and “age”) on manual dexterity and found that “age” had a significant impact on manual dexterity; Li et al. [7] chose three factors, namely the subjects’ “dominant hand,” “experience of learning musical instruments” and “gender,” for analysis and found that the interaction between “dominant hand” and “experience of learning musical instruments” had a significant impact, while “gender” had no significant impact on manual dexterity. Li et al. [8] chose two factors, namely “accepting training for musical instruments” and “character,” and questioned the validity of BD-II-601 manual dexterity testing instruments, according to the fact that the factor of “accepting training for musical instruments” had no significant impact and the factor of “character” had significant impact. From the above studies, we can see that researchers have made some achievements in exploring the influencing factors of manual dexterity. However, some studies neither take into account the impact of extreme values in the experimental data processing stage, nor adopt specific statistical and testing methods for further analysis. In addition, the factors selected by some research institutes are demographic variables, such as “gender” and “age,” which cannot be changed through acquired training, so that it is difficult to help us put forward specific suggestions on improving manual dexterity. Other researchers, such as Li et al. [8] regard “character” as an interference factor in manual dexterity test. They drew a conclusion that the “test results from BD-II-601 manual dexterity testing instruments are not credible.” The rationality of this conclusion is also worth further exploring. On this basis, this study hopes that the work of two aspects can be completed: Firstly, a series of studies are carried out by virtue of BD-II-601 manual dexterity testing instruments in ergonomics laboratories of universities and two comprehensive evaluation parameters of manual dexterity are constructed; secondly, whether “character” is a factor affecting manual dexterity is analyzed. It is also hoped that appropriate measures can be taken to try to eliminate its interference with the experimental results. Compared with previous studies, this study hopes to achieve some results in the following aspects: Firstly, the study constructs two new comprehensive evaluation parameters and simplifies the experiment, while ensuring the objectivity and reliability of the experiment; secondly, according to the two comprehensive evaluation parameters, reasonable classification is realized for the subjects; thirdly, in view of the deficiency that “experimental data processing and analysis stage is too abbreviated” in some previous studies, this study adopts some new statistical and testing methods to analyze and discuss the experimental data in more detail; finally, based on the experimental research, this study puts forward some specific suggestions on improving human’s manual dexterity, which is of certain reference value for enterprises to be engaged in safety management and accident prevention, so as to achieve safety in production, select suitable employees and train staff reasonably.

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2 Design of Experiment 2.1

Conditions of Subjects

A total of 83 subjects were randomly selected from a university in Nanjing. They are 18–20-year-old college students not majoring in athletics. The proportion of males to females were approximately the same (according to the research of Zhao et al. [6] and Li et al. [7], the impact of gender difference on manual dexterity was not statistically significant, so that this study did not analyze the differences of gender impact). In addition, all subjects had never contacted a similar test or manual dexterity testing instruments before this study.

2.2

Experimental Process and Precautions

In this study, this hypothesis was tacitly approved at first: The test results of some typical manual dexterity testing instruments produced in the domestic market can truly reflect the manual dexterity of the subjects. In this study, BD-II-601 manual dexterity testing instruments [9] produced by Beijing Qingniaotianqiao Instrument and Equipment Co., Ltd., were adopted to test all the subjects in turn, according to the steps specified in the instructions for use of the instrument. The header of the record table of original experimental data includes the following two items: the serial number of the subjects (1–83 for this study) and the total time T (unit: s). The precautions during the experiment are as follows: 1. The experimenter only arranges one test for each subject. The reasons are as follows: According to the results of Li et al. [8], different subjects’ results will improve at different levels if they are asked to take the exact test again; the subjects’ results of the second test may be affected by the fatigue caused by the first test. 2. The experimenter must pay special attention to the following points to ensure reliability of the experiment. • Before the test, in order to make the subjects give full play to their personal level, the experimenter should use encouraging words, such as “try your best to minimize the total time of inserting 100 sticks”. • Before the test, remind all the subjects, “Don’t be nervous, behave boldly, and don’t care if someone else is present”. • During the test, the experimenter should not use prompting words and actions. • The experimenter shall ask the present subjects not to make noise and prevent other people from intruding into the laboratory without authorization. • The experiment was carried out from 9:00–11:00 a.m. and the environmental factors, such as temperature and lighting, were basically the same.

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3. The experimenter must also give the following supplementary instructions for the experimental operation and require all the subjects to comply with them. • After the experiment was officially started, the subjects’ postures of holding tweezers with their dominant hands may be slightly different as long as they felt comfortable. However, the position of holding the stick with the tweezers was unified near the central position of the stick. • During the whole test, the subjects’ body postures were unified as standing and bending. • The subjects need to insert each stick into the bottom of the round hole in the BD-II-601 manual dexterity testing instrument’s panel. If a subject drops a stick midway, intentionally or unintentionally, he/she should immediately pick it up with the tweezers to continue stick insertion without putting it back into the slot on the left of the instrument’s panel.

3 Analysis of Experimental Results 3.1

3.1.1

Construction of Two Comprehensive Evaluation Parameters Proposition of Two Comprehensive Evaluation Parameters

According to everyday experience, people with certain capabilities (such as piano practicing) are generally believed that they have higher manual dexterity. The problem is that this general sense of higher manual dexterity does not necessarily mean better test results on experimental instruments of manual dexterity. On this basis, this study combines the existing data and interviews with some college students to find out the specific capability indexes (hereinafter referred to as sub-parameters) that people generally think can reflect manual dexterity, such as fluency in pen spinning and time of piano practicing. The acquisition processes of some sub-parameters are unbearable to the general public because the price of relevant equipment and the training fee are too high or the long time and great efforts are needed. Therefore, these sub-parameters are classified as a comprehensive evaluation parameter, which is called “artistic capability”; the remaining sub-parameters are classified as another comprehensive evaluation parameter, that is, “general athletic capability.”

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3.1.2

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Questionnaire Survey and Grouping of Subjects

Based on the above two comprehensive evaluation parameters, the experimenter first designed a questionnaire to classify the subjects. The questionnaire contains two above-mentioned comprehensive evaluation parameters: “general athletic capability” and “artistic capability,” each of which contains a series of sub-parameters. “general athletic capability” includes eight items: being able to dribble the basketball without looking at it frequently with eyes; spinning the pen fluently with fingers; hardly ever dropping food/easily picking up food when using chopsticks; typing on the keyboard without looking at it frequently and with a high accuracy; smoothly assembling some mechanical equipment such as aircraft models; being able to use abacus; being able to do finger gymnastics; high APM in writing with pens and playing games. “Artistic capability” includes four items: being able to play stringed instruments; being able to play wind instruments; being able to draw; being able to knit. In addition, the questionnaire also recorded the character of each subject (character is divided into introversion/extroversion, which is judged by the subjects themselves). Then, the following three hypotheses were put forward: All the sub-parameters have the same weight and are independent of each other; the subjects can get one point for each of the sub-parameters that they think they conform to. The higher the score is, the stronger their capability will be. The influence of the sub-parameters not listed was neglected. Then, here came the specific grouping methods: “general athletic capability” and “artistic capability” each has two levels, namely “strong” and “weak.” When the score for “general athletic capability”  3, it is “strong”; when the score is 0–2, it is “weak.” When the score for “artistic capability”  1, it is “strong”; when the score is 0, it is “weak.” According to the survey results, 83 subjects were divided into four groups and their names are explained as follows: • Group with Strong “General Athletic Capability” and Strong “Artistic Capability” (Group A): namely the group of subjects with strong “general athletic capability” and strong “artistic capability”; • Group with Weak “General Athletic Capability” and Weak “Artistic Capability” (Group B): namely the group of subjects with weak “general athletic capability” and weak “artistic capability”; • Group with Weak “General Athletic Capability” and Strong “Artistic Capability” (Group C): namely the group of subjects with weak “general athletic capability” and strong “artistic capability”; • Group with Strong “General Athletic Capability” and Weak “Artistic Capability” (Group D): namely the group of subjects with strong “general athletic capability” and weak “artistic capability”. According to the character (introversion/extroversion) of the subjects in each group, the results were separately summarized as follows: There were 24 persons in

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Group Group Group Group

A, including 13 introverts and 11 extroverts; there were 16 persons in B, including 12 introverts and 4 extroverts; there were 25 persons in C, including 12 introverts and 13 extroverts; there were 18 persons in D, including 11 introverts and 7 extroverts.

3.1.3

Intuitive Inspection for the Rationality of Grouping of Subjects

In order to test the rationality of the above grouping method, the abnormal values of the data were evaluated at first. The data of total time T (the time for each subject to complete the manual dexterity test on the BD-II-601 manual dexterity testing instrument) in four groups was adopted to draw the boxplots, as shown in Fig. 1. The abnormal values were evaluated according to the boxplots and Grubbs test method (a = 0.05). The result is that the test result of one subject (T = 1097 s) needs to be eliminated and 82 data can remain. After eliminating the abnormal value and calculating the mean value of the total time T for each group, we can find that the mean value of the total time T of Group A changed from 613.2 to 592.2 s which is the minimum among the four groups’ mean values; the mean value of the total time T of Group B (742.8 s) is the maximum value; the mean values of the total time T of the remaining two groups (628.1, 598.2 s) are in the range of 592.2 to 742.8 s. Similar relationship can also be obtained if the mid-values (medians) of total time T of the four groups are adopted for intuitive test. The above discussion intuitively proves that the higher the scores of the two comprehensive evaluation parameters are, namely the better the manual dexterity in general sense is, the better the results of the corresponding manual dexterity instrument test will be. That is also consistent with common sense. Therefore, the two comprehensive evaluation parameters constructed are reasonable and the method of dividing all the subjects into four groups based on the former is also reasonable.

1150.0 1050.0

1097.0

1057.0 979.3

950.0 850.0

789.9

750.0

716.7

650.0 550.0 450.0 350.0

578.9

602.8

591.5

422.4

434.0

527.7

393.6

Fig. 1 Four boxplots of experiment data from four groups

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165

Two-Factor Unequal Repeated Measures ANOVA

In order to explore whether there are significant differences between the two comprehensive evaluation parameters, namely “general athletic capability” and “artistic capability,” on manual dexterity, this study adopted two-factor unequal repeated measures ANOVA (two factors, namely “general athletic capability” and “artistic capability,” have two levels, respectively, namely “strong” and “weak”; the experimental index is the total time T; a = 0.05). The following is a discussion on whether the preconditions of the test are satisfied: Independence requires that 82 experimental data in the whole sample shall be independent of each other. Since the experimenter had made a relatively strict control of the experimental environment before the experiment began and each subject was tested independently without affecting each other, the conditions were satisfied. Normality requires that the experimental data in each factor-level combination (each group) must obey the normal distribution. Shapiro–Wilk test was adopted to test the normality of the total time T (a = 0.05) of the four groups in turn. The results were as follows: Group A: p = 0.415 > 0.05; Group B: p = 0.095 > 0.05; Group C: p = 0.036 < 0.05; Group D: p = 0.858 > 0.05. Except for Group C, the experimental data of the other three groups meet the requirements for normal distribution. Normal Q–Q chart of all the experimental data of Group C are as shown in Fig. 2. It is known from Fig. 2 that most of the data are near the straight line, except for the two values on the right end which deviate from the straight line to a great extent. However, according to the discussion of Sect. 3.1.3 on the elimination of abnormal values, the two values shall be retained. Therefore, it is considered that all the experimental data in Group C can approximately satisfy the requirements for normal distribution. Finally, the Homogeneity of Variance requires that each level combination must satisfy the requirements for homogeneity of variance. The results of test for homogeneity of variance are shown in Table 1. It is known from the column of significance that p = 0.552 > 0.05, so that the homogeneity of variance is satisfied. 3

Expected normal value

Fig. 2 Normal Q–Q figure of experiment data from Group C (weak “general athletic capability” and strong “artistic capability”)

2 1 0 -1 -2

400

600

800

T/s

1000

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Table 1 Levin test for the variance of error Dependent variable: T F value Degree of freedom-1

Degree of freedom-2

Significance

0.705

78

0.552

3

To sum up, while the condition of normality was slightly unsatisfactory, the other two conditions were well satisfied, so that the two-factor unequal repeated measures ANOVA can still be carried out. By analyzing the output results of SPSS 24.0 software, we can draw the preliminary conclusions as follows: In the “revised model” p = 0.003 which is much less than 0.01, which shows that the established statistical model is very reasonable; in the interaction between “general athletic capability” and “artistic capability,” p = 0.066 which is greater than 0.05, which shows that the influences of the two on total time T are independent. Next, the model can be simplified by ignoring the effect of interaction. Then, SPSS 24.0 software shall be adopted again to conduct two-factor unequal repeated measures ANOVA. The following conclusions can be drawn: The main effect of “revised model” shall be very significant (p < 0.01), which indicates that the statistical model established is very reasonable; the main effect of “general athletic capability” is very significant (p < 0.01), which indicates that it has a very significant effect on total time T; the main effect of “artistic capability” is significant (p < 0.05), which indicates that it has a significant effect on the total time T. To sum up, statistically, the comprehensive evaluation parameter “general athletic capability” has a very significant impact on manual dexterity.

3.3

Hypothesis Testing Related to Character Factors

In the study of Li et al. [8], the discussion about “the influence of ‘character’ on manual dexterity” is representative. There are two main viewpoints: Human’s manual dexterity cannot be determined by character, so that “character” shall be regarded as a non-relevant interference factor of test results of manual dexterity testing instruments; follow-up statistical test results show that manual dexterity is not correlated to character, so that the influence of interference factor “character” on instrument test results is statistically significant, that is, the anti-interference capability of the instrument is weak, which needs to be improved. Through the above research and analysis, this study considers that it is reasonable and feasible to regard character as an interference factor rather than an influence factor. In addition, this study adopts means of statistical test, namely judges whether there is significant difference in mean value of total test time T among the subjects with different personalities in the four groups successively through two-sample t test (a = 0.05).

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The following is a discussion on whether the preconditions of the test method are satisfied. Independence requires that 82 experimental data in the whole sample shall be independent of each other. Since the experimenter had made a relatively strict control of the experimental environment before the experiment began and each subject was tested independently without affecting each other, the condition was satisfied. Normality requires that all subgroups come from a normally distributed population. The “exploration” process in SPSS 24.0 software was used to conduct Shapiro–Wilk tests (a = 0.05) for the data of two subgroups divided according to the introversion/extroversion in each group. The results are as follows: For Introversion Subgroup of Group A: p = 0.639 > 0.05, for Extroversion Subgroup of Group A: p = 0.609 > 0.05; for Introversion Subgroup of Group B: p = 0.303 > 0.05, for Extroversion Subgroup of Group B: p = 0.282 > 0.05; for Introversion Subgroup of Group C: p = 0.892 > 0.05, for Extroversion Subgroup of Group C: p = 0.005 < 0.05; for Introversion Subgroup of Group D: p = 0.898 > 0.05, for Extroversion Subgroup of Group D: p = 0.448 > 0.05. Among them, all the data of two subgroups divided according to the personality (introversion/extroversion) of subjects in Group A, Group B and Group D meet the requirements for normal distribution. However, the data of Group C do not meet the requirements. According to the principle of sample size equalization [10], that is, when the sample contents of two samples are basically equal, as long as the ratio of variances between the two samples (larger: smaller) is less than 3, the adverse effects caused by using the test method when the normality is not satisfied can be compensated to a certain extent. Introversion Subgroup of Group C has 12 data about the total time T. Extroversion Subgroup of Group C has 13 data about the total time T. The sample content is approximately equal; according to the calculation, the ratio calculated was slightly greater than 1. Therefore, conditions for normality were also satisfied. Then, two-sample t test was conducted for the data of two subgroups divided according to the character (introversion/extroversion) in each group. The results are as follows: Group A: p = 0.601 > 0.05; Group B: p = 0.137 > 0.05; Group C: p = 0.262 > 0.05; Group D: p = 0.377 > 0.05. The four p values are all greater than 0.05, which indicates that there is no significant difference in the total time T for extravert and introvert subjects to complete the test in each group, which indicates that extravert subjects’ results of manual dexterity test are not always better than those of introvert subjects. Therefore, the measures taken by the experimenter to eliminate the influence of personality have been proved to be effective and there is no need to improve the BD-II-601 manual dexterity testing instruments accordingly.

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4 Conclusions The main conclusions of this study are as follows: (1) “Character” shall be regarded as an interference factor rather than a general influence factor in the manual dexterity experiment. (2) This study constructs two comprehensive evaluation parameters, namely “general athletic capability” and “artistic capability,” which simplify the factors affecting human’s manual dexterity that need to be considered without losing objective rationality. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of College of Safety Science and Engineering, Nanjing Tech University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Wang B, Wang X, Liu S et al (2007) Safety ergonomics. China Machine Press, Beijing 2. Shu H, Lu D (1996) Test and evaluation on the occupational adaptability of driving mobile equipment in factories. Chin J Ergon 2(3):1–4 3. Luo Y (2013) Introduction to safety science. China Zhijian Publishing House, Beijing 4. Li S, Song S, Chen Y (2009) Evaluation of occupational safety adaptability. Prod Res 15:135–137 5. Wu K, Zhang B, Yao H (1997) Strategy and method for studying the professional adaptability for operators of dangerous installation. China Saf Sci J 7(4):17–22 6. Zhao D, Li J, Guan W et al (2010) Experimental analysis of factors of manual dexterity. In: Proceedings of 2010 (Shenyang) International Colloquium on Safety Science and Technology, 2010, pp 374–378 7. Li Z, Yang M, Huo Y et al (2013) Research on factors that affect manual dexterity of college students. Hina Sci Technol Panor Mag (24):226–227, 230 8. Li Y, Wu H (2006) The result reliability study on BD-II-601 finger-agility-meter. Res Explor Lab 25(10):1213–1217 9. Beijing qingniaotianqiao Instrument & Equipment Co., Ltd. (2018) Instruction for psychological instruments of BD-II Series [internet]. The Co., Ltd., Beijing 2018 May [Cited 2018 Sept 26] Available from: www.pkuie.com.cn/BD2/BD2-xinli.pdf 10. Zhang W (2017) Basic course of SPSS statistical analysis, textbooks for colleges and universities, 3rd edn. Higher Education Press, Beijing

Sniper Selection Index Measurement and Factor Weight Analysis Weiming Deng, Yubo Deng, Liwei Gong, Lu Hua, Shikun Wang and Fei Ji

Abstract There is a problem that the proportion of qualitative selection is larger than that of quantitative selection in the selection process of our army’s snipers. In this study, the methods of testing and mathematical statistics were used to analyze the sniper material selection index quantitatively, and the weight of each index was determined through calculation, so as to further build a complete sniper material selection index system. Finally, four main factors were determined, which were stability factor, shooting ability factor, respiration factor and mental factor, which break the traditional mode of selecting sniper based on the form, function, quality and psychology. Keywords Sniper


Selection
Measurement
Factor analysis

Sniper is a highly specialized post. The modern technology makes the sniper perform extremely excellent just like a tiger which has got wings. An outstanding sniper can damage the enemy as a conventional combat detachment which is costly [1]. Thus, it is emergent for the army to find the method for selecting excellent sniper talents and improving the sniper training effect according to the combat mission characteristics. The study used the mathematical statistics method, testing method, etc., to quantitatively investigate key indexes for sniper selection [2].

W. Deng
Y. Deng
L. Gong
L. Hua
S. Wang
F. Ji (&) Special Operations Academy of PLA, Guangzhou 510500, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_20

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1 Study Subjects and Method 1.1

Test Subjects

The subjects are the snipers from navy, land army and air force of PRC, who are healthy men and have participated in sniper training of the whole army in 2011, 74 effective samples are included.

1.2 1.2.1

Study Method Mathematical Statistics Method

The study used average, standard deviation, factor analysis, gray correlation analysis, method of percentiles and other mathematical statistics methods for reorganizing and statistically analyzing relevant data acquired during measurement with the SPSS 17.0 statistic software package. The questionnaire survey results and all index test data of the sniper were inputted in Microsoft Excel. The mathematical statistics is processed by the SPSS 17.0 software package, and factor analysis was used for analyzing the principal component characteristic value, variance contribution rate and accumulated contrition rate so as to classify all indexes. In addition, the gray correlation analysis (gray system theory) was used for analyzing the importance of all indexes during sniper selection.

1.2.2

Measurement Method

During measurement, the study used diversified instruments and measurement methods for testing the indexes of the 74 snipers’ upper limb stability, static endurance, breath-holding ability, emotional stability, 100 m precision shooting and 150 m precision shooting and got data [3].

2 Study Results and Analysis The 12 items screened out from questionnaire survey, namely, hand length, upper limb length, shoulder width, vital capacity/body weight, upper limb stability, static endurance, breath-holding ability, attention, emotional stability, nerve type, 100 m precision shooting and 350 m precision shooting, which are important for sniper selection, are used as the test indexes to test the 74 snipers who have participated in sniper training of the whole army in 2011, and statistical analysis was carried out to the results [4].

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Test Results of Quantitative Indexes

See Table 1.

2.2

Factor Analysis Result of Indexes of Sniper Selection

Factor analysis was used in the study in order to classify the indexes early screened out into main factors so as to determine the weight of each index through calculation, and then further construct the completed index system for sniper selection. Generally, the factor analysis comprises of the following steps: ① calculation of relevant matrices; ② factor extraction; ③ factor rotation; ④ calculation of factor score; and ⑤ interpretation of the factor. The study carried out factor analysis to the measurement results of the following six indexes, namely X1 upper limb stability, X2 static endurance, X3 breath-holding ability, X4 emotional stability, X5 100 m precision shooting and X6 350 m precision shooting. The study analyzed the characteristic values and contribution rates of all indexes and found out main factor of these indexes. Different from the results of the other measurement indexes, the attention measurement result is the type, thus, factor analysis is not applicable. At first, the measurement data were tested for factor analysis applicability. KMO and Bartlett spherical detection were carried out to the measurement results of the six indexes of the 74 snipers. KMO statistical quantity is mainly used for detecting the partial correlation among variables. It makes comparison of the simple correlation and partial correlation degree among all variables, and the values are from 0 to 1. If there is the internal correlation among all variables, latent variables are controlled at the same time when control the other factors during the calculation of partial correlation; thus, the partial correlation coefficient is far more smaller than the simple correlation coefficient and then the KMO statistical quantity at this time Table 1 Statistical table of quantitative index test results of sniper selection (n = 74) Indicators Upper extremity stability (number) static endurance (s) Breath-holding ability (s) Emotional stability 100 m precision Shooting (round) 350 m precision shooting (round)

Maximum value

Minimum value

Average (x)

Standard deviation (s)

8

2

5.39

1.23

448 137

308 22

372.15 57.51

21.47 22.57

39 94

9 62

22.62 76.87

6.22 5.03

46

12

28.18

4.74

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is close to 1, using factor analysis will get a good effect. Generally, it believes the factor analysis is the best when KMO is higher than 0.9, proper when KMO is 0.8– 0.9, tolerable when KMO is 0.7–0.8, not proper when KMO is 0.6–0.7, and not allowed when KMO is lower than 0.5. Bartlett spherical detection is used for detecting whether relevant matrices are unit matrices, namely, whether all variables are separately independent [5]. The analysis result indicated the data KMO was 0.896, which meant these data were applicable for factor analysis. The result of the Bartlett spherical detection was 3216.142, P < 0.001; thus, the null hypothesis of the Bartlett spherical detection was refused. It meant the six variables were not independent. Thus, factor analysis was applicable (Table 2). The following method was used for determining the factor number. Whether the characteristic value was higher than 1 was used as the standard. The number of the characteristic roots when the characteristic value was higher than 1 was the extracted factor number which made the accumulated variance contribution rate of the first factors reaches a proper proportion which is generally 80%. As shown in Table 3, the accumulated contribution rate of the first three principal components is 83.29% which is higher than 80% while the characteristic value of the 4th component is smaller than 1. Thus, the study selected three main factors. As shown in Table 4, the study selected three factors which interpreted 83.29% of all variables. The variance contribution rate after rotation can be used as the weight of the factor. Before the factor load matrix rotated, the indexes of upper limb stability and breath-holding ability had high loads on two or more than two factors, which made the actual meaning of the three factors vague. Thus, orthogonal rotation was carried out to the factor load matrix. After orthogonal rotation, indicated by Table 5, the Table 2 KMO and Bartlett’s test (n = 74) (KMO and Bartlett’s spherical test results) Kaiser-Meyer-Olkin Bartlett’s spherical degree inspection

Measure of sampling adequacy Approximate chi square Df p

0.896 3216.142 80 0.000

Table 3 Main ingredients list Divisor

Initial eigenvalue Eigenvalue Variance contribution (%)

Cumulative (%)

Upper extremity stability X1 Static Endurance X2 Breath-holding ability X3 Emotional stability X4 100 m precision shooting X5 350 m precision shooting X6

4.479 2.371 1.976 0.938 0.869 0.651

39.58 74.54 83.29 90.96 96.74 100.00

39.58 34.96 8.75 7.47 5.98 3.26

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Table 4 Factor eigenvalue and variance contribution rate before and after rotation Original variance

Variance after rotation

Divisor

Eigenvalue

Variance contribution (%)

Cumulative (%)

Eigenvalue

Variance contribution (%)

Cumulative (%)

Divisor 1

4.479

39.58

39.58

3.958

37.77

37.77

Divisor 2

2.371

34.96

67.54

2.289

33.68

71.45

Divisor 3

1.976

8.75

83.29

2.179

11.84

83.29

Table 5 Factor load matrix after rotation Indicators

Divisor 1

Divisor 2

Divisor 3

Upper extremity stability X1 Static endurance X2 Breath-holding ability X3 Emotional stability X4 100 m precision shooting X5 350 m precision shooting X6

0.757 0.626 0.162 −0.672 0.264 0.299

0.346 0.317 0.579 −0.366 0.765 0.716

0.117 0.262 0.672 −0.254 0.329 0.287

indexes of upper limb stability, static endurance and emotional stability had high loads on the first factor. The first factor mainly interprets stability; thus, the study named it as the stability factor. The 100 m precision shooting and 350 m precision shooting had high loads on the second factor, and the loads of the breath-holding ability on the second and third factors were, respectively, 0.579 and 0.672, but the control of factor structure and specific items found some individual indexes had differences of semantic consistency with the other indexes in belonging elements. In this condition, if improper items are classified in one factor, and there are also high or close load values on the other factors, the index shall be classified as the logical factor for corresponding adjustment. Thus, combining with the other indexes, the breath-holding ability was classified as the third factor. The second factor mainly interprets the shooting ability; thus, the study named it as the shooting ability factor. The breath-holding ability had a high load on the third factor. The third factor interprets the respiratory ability; thus, the study named as the respiratory factor. To sum up, three factors, namely stability factor, shooting ability factor and respiratory, were obtained after carrying out factor analysis to the measurement data of indexes of sniper selection [6]. Nerve type and attention are also important indexes for sniper selection but they were not measured and could not undergo factor analysis during the experiment, they can be classified as metal factor from their semantic meanings and types. Thus, at last, the stability factor, shooting ability factor, respiratory factor and mental factor are the indexes for sniper selection [7, 8]. With factor analysis, the weights of the three factors were the variance contribution rates after rotation, which respectively were stability factor 37.77%, shooting

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Table 6 Sniper selection index four-factor model Factor name

Variance contribution (%)

Indicator content

Stability factor

37.77

Shooting capability factor

33.68

Respiratory factors Mental factors

11.84 16.71

Upper extremity length, static endurance, emotional stability 100 m precision shooting, 350 m precision shooting Breath-holding ability Neurological type, attention

ability factor 33.68% and respiratory factor 11.84%, they were 83.29% of the total weight, and the weight of the mental factor was 16.71%. The four-factor model of indexes of sniper selection is shown in Table 6.

3 Conclusion The study applied factor analysis to the measurement data of the six indexes of the 74 snipers who have participated the sniper training of the whole army in 2011 and found out four main factors which are the stability factor, shooting ability factor, respiratory factor and mental factor. The indexes contained by and weights of all factors were determined by using the variance contribution rates after rotation in factor analysis and the factor load matrix. The study established the four-factor model of indexes of sniper selection according to the combat mission characteristics, breaks through the traditional four-element (body physique, function, fitness and psychological quality) mode of sniper selection, provides a new idea for further perfecting the system of sniper selection and used the statistical analysis of trusted data to support its theoretical basis. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Special Operations Academy of PLA. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Yubing Y, Xianqian W (2011) Sniper basic course. Huangshan Book Society, p 7 2. Wang J (2003) Principles and methods of athlete selection. Beijing sport University Press, Beijing 3. Hanhan H Sniper training materials, p 78–79 4. Yongrui L, Chengmou L, Houcan Z (2005) Research on characteristics of attention ability of high-level athletes in different sports. Sports Sci 25(3)

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5. Du L (2000) Stability is the basic condition for the material selection of shooters. China New Technol New Prod (3) 6. Xiuli, Z, Xiangdong W, Xuezhen L (2007) Characteristics and evaluation indexes of balance stability of national elite shooters. J Phys Educ 14(2) 7. Spicer M (2006) Illustrated manual of sniper skills 8. Hatfield B, Haufler A, Contreras-Vidal J (2007) Brain processes and neurofeedback for performance enhancement of precision motor behavior. Department of Kinesiology University of Maryland, College Park

Investigation on the Index of Sniper Selection and Gray Correlation Analysis Zhiwei Zhu, Weiming Deng, Bing Zhang, Shandong Mao and Chan Zhang

Abstract There is a problem that the proportion of qualitative selection is larger than that of quantitative selection in the selection process of our army’s snipers. This research adopts the methods of questionnaire, mathematical statistics and testing, and balanced qualitative analysis and quantitative analysis to analyze the investigation and test objects, to determine the importance of each index in the selection of snipers, and to determine its different weights, which including upper limb stability, nerve type, attention, 350-m accuracy shooting, emotional stability, static endurance, 100-m accuracy shooting, breath-holding capacity, hand length, lung capacity/body weight, upper extremity length, shoulder width, etc. Keywords Sniper


Selection
Index
Gray correlation

The snipers who have been professionally trained are the most dangerous and difficult to cope with. They have been rigorously trained and can effectively snipe the enemy within 1000 m. They are brilliant in the decapitation strike and play a huge function for blocking the operational effectiveness of a company unit. They can precisely interrupt the combat of the company. Their influence increases with the increase of the casualties brought by them [1]. Thus, it is emergent for the army to find the method for selecting excellent sniper talents and improving the sniper training effect according to the combat mission characteristics. The study used the questionnaire survey, mathematical statistics method, testing method, etc., to quantitatively and qualitatively investigate key indexes of sniper selection [2].

Z. Zhu
W. Deng
B. Zhang
S. Mao
C. Zhang (&) Special Operations Academy of PLA, Guangzhou 510500, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_21

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1 Study Subjects and Methods 1.1 1.1.1

Study Subjects Subjects of Questionnaire Survey

A total of 30 sniper coaches from a special force and the training corps of a division are the subjects of questionnaire survey, among which 19 have been serving as coaches for more than 10 years as well as 7 for 6–9 years and 4 for less than 6 years.

1.1.2

Test Subjects

The subjects are the snipers from navy, land army, and air force of PRC, who are healthy men and have participated in sniper training of the whole army in 20XX, 74 effective samples are included.

1.2 1.2.1

Study Methods Questionnaire Survey

Questionnaire design: The Questionnaire for Investigating Indexes of Sniper Selection was designed in accordance with the study content and purpose of the topic, basic requirements of research methods in sports science, and detailed analysis of sniper missions. In the study, 30 questionnaires were distributed and 30 questionnaires were collected. The collection rate was 100%. There were 30 effective questionnaires, and the effective collection rate was 100%.

1.2.2

Mathematical Statistics Method

The study used average, standard deviation, factor analysis, gray correlation analysis, method of percentiles, and other mathematical statistics methods for reorganizing and statistically analyzing relevant data acquired during measurement with the SPSS 17.0 statistic software package. The questionnaire survey results and all index test data of the sniper were inputted in Microsoft Excel. The mathematical statistics is processed by the SPSS 17.0 software package, and factor analysis was used for analyzing the principal

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component characteristic value, variance contribution rate and accumulated contrition rate so as to classify all indexes. In addition, the gray correlation analysis (gray system theory) was used for analyzing the importance of all indexes during sniper selection and determining the weights.

1.2.3

Measurement Method

During measurement, the study used diversified instruments and measurement methods for testing the selected indexes of the 74 snipers and got data.

2 Study Results and Analysis 2.1

Analysis of Questionnaire Survey Results

The study made the Questionnaire for Investigating Indexes of Sniper Selection with the indexes of sniper selection by combining with the characteristics of sniper missions [3]. The questionnaire comprises of literature summary and 24 indexes obtained after analyzing the sniper missions, i.e., body height, body weight, upper limb length, hand length, forefinger length, shoulder width, hand width, pull-ups, push-ups, simple reaction time, vital capacity, vital capacity/body weight, breath-holding ability, hand movement stability, static endurance, maximum oxygen uptake, anti-jamming ability, basic heart rate, nerve type, emotional stability, attention, forced sense, 100-m precision shooting, and 350-m precision shooting. The important degrees of the 24 indexes are classified into five classes, namely very important, important, relative important, common, and unnecessary. The coaches should click “√” under the corresponding important degree. Delphi method was used for assigning values of 5 scores to very important, 4 scores for important, 3 scores for relative important, 2 scores for common, and 1 score for unnecessary during the analysis. The weighted average of each index was calculated [4, 5]. The calculation method is as follows: [(people number of very important  5) + (people number of important  4) + (people number of relative important  3) + (people number of common  2) + (people number of unnecessary  1)]/30. Then, select the indexes of which the weighted averages were higher than or equal to 4, namely the important degree was relatively important and above, as the indexes of sniper selection. Then, the data in the following table were obtained (Table 1). Twelve indexes of which the important degrees were higher than 4.0 were preliminarily selected with the questionnaire survey statistics. The indexes were hand length, upper limb length, shoulder width, vital capacity/body weight, upper limb stability, static endurance, breath holding ability, attention, emotional stability, nerve type, 100-m precision shooting, and 350-m precision shooting.

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Table 1 Statistical table of questionnaire results of sniper selection index Indicators

More important

Important

Less important

General

Indifferent

Score

Body height Body weight Upper limb length Hand length Forefinger length Shoulder width Hand width Pull-ups Push-ups Simple reaction time Vital capacity Vital capacity/body weight Breath-holding ability Hand movement stability Static endurance Maximum oxygen intake Anti-jamming ability Basic heart rate Nerve type Emotional stability Attention Forced sense 100-m precision shooting 350-m precision shooting

2 0 16 15 6 12 9 8 7 10 7 11

3 1 8 11 14 10 10 8 4 11 3 12

4 4 3 2 3 5 3 10 10 4 10 4

17 15 3 1 6 3 6 3 8 4 9 2

4 10 0 1 1 0 2 1 1 1 1 1

2.40 1.87 4.23 4.27 3.60 4.03 3.60 3.63 3.26 3.83 3.20 4.00

13

10

4

3

0

4.10

18

11

1

0

0

4.57

17 9

8 14

4 4

1 1

0 2

4.37 3.90

10 6 14 13 17 10 11

7 8 10 13 10 5 15

7 13 5 3 0 11 3

5 1 1 1 3 2 1

1 2 0 0 0 2 0

3.67 3.50 4.23 4.27 4.37 3.63 4.20

12

13

5

0

0

4.23

2.2

Test Results and Analysis of Indexes

The 12 items screened out from questionnaire survey, namely hand length, upper limb length, shoulder width, vital capacity/body weight, upper limb stability, static endurance, breath-holding ability, attention, emotional stability, nerve type, 100-m precision shooting and 350-m precision shooting, which are important for sniper selection, are used as the test indexes to test the 74 snipers who have participated sniper training of the whole army in 20XX, and statistical analysis was carried out to the results [6] (Table 2).

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Test Results of Quantitative Indexes

Table 2 Statistical table of quantitative index test results of sniper selection (n = 74) Indicators

Maximum Value

Minimum value

Average (x)

Standard deviation (s)

Upper limb length (cm) Hand length (cm) Shoulder width (cm) Vital capacity/body weight (index) Upper limb stability (number) Static endurance (second) Breath-holding ability (second) Emotional stability 100-m precision shooting (round) 350-m precision shooting (round)

82.00 20.40 50.00 82.67 8 448 137 39 94 46

62.00 17.00 37.50 60.67 2 308 22 9 62 12

73.43 18.72 41.07 71.91 5.39 372.15 57.51 22.62 76.8 28.18

3.16 0.81 2.03 3.74 1.23 21.47 22.57 6.22 5.03 4.74

2.3

Results of Gray Correlation Analysis of Test Indexes

Gray correlation is the measurement for describing the correlation degree of data sequences and has the characteristic of overall measurement. For further refining, the 12 indexes which were preliminarily screened out by the questionnaire and sorting the important degrees of the 12 indexes with the mathematical quantification method, and the gray correlation analysis can be just used for combining with the measurement results of the 12 indexes to sort the important degrees of the indexes [7]. Took the comprehensive record (X0) of sniper assessment as the reference sequence, and the test data of the 12 indexes (X1–X12) of sniper selection as the comparison sequence, input them into the 1.0 gray correlation analysis software of gray-system-theory, wherein, the nerve types were, respectively, scored as 4, 3, 2, and 1 in accordance with A, B, C, and D and the attention was, respectively, scored as 4, 3, 2, and 1 in accordance with A, B, C, and D [8, 9]. The indexes had different dimensions; thus, they cannot be compared. Thus, all data were non-dimensionalized, namely normalized before calculating the correlation coefficient. Raw data were standardized according to the following formula (Tables 3 and 4): Xi0 ðKÞ

 ¼

Xi ð2Þ Xi ð3Þ Xi ðkÞ ; ;... 1; Xi ð1Þ Xi ð1Þ Xi ð1Þ



At last, the 1.0 gray correlation analysis of gray-system-theory was used for calculating out the correlations of all indexes, and correlations were sorted. Table 5

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Table 3 Sniper indicators raw data Number of subjects

Upper extremity length X1

Hand length X2

Shoulder width X3

Pulmonary/ weight X4

Upper extremity stability X5

Static endurance X6

Breath holding ability X7

Optimal data

82

20.40

50

82.67

8

448

137

1

73

19.5

41

64.7

6

376

54

2

74.5

18.6

45

70.2

5

403

37

3

74

19.2

41

77.9

4

352

88

4

78

20.2

40.5

68.1

5

395

38

…

…

…

…

…

…

…

…

74

75

18.7

43

Number of subjects

Emotional stability X8

100 m precision shooting X9

350 m precision shooting X10

Neurological type X11

Attention X12

Comprehensive result X0

Optimal data

9

94

46

4

4

854.25

1

32

79

35

3

3

479.5

2

18

64

28

4

3

668

3

21

87

40

3

2

660.75

4

21

82

29

1

3

652.25

…

…

…

…

…

…

…

74

24

86

37

3

2

629.75

76.4

7

412

85

Table 4 Sniper indicators normalized data Number of subjects

Upper extremity length X1

Hand length X2

Shoulder width X3

Pulmonary/ weight X4

Upper extremity stability X5

Static endurance X6

Breath holding ability X7

Optimal data

1

1

1

1

1

1

1

1

0.89

0.96

0.82

0.78

0.75

0.84

0.39

2

0.91

0.91

0.9

0.85

0.63

0.90

0.27

3

0.90

0.94

0.82

0.94

0.5

0.79

0.64

4

0.95

0.99

0.81

0.82

0.63

0.88

0.28

…

…

…

…

…

…

…

…

74

0.91

0.92

0.86

Number of subjects

Emotional stability X8

100 m precision shooting X9

350 m precision shooting X10

Neurological type X11

Attention X12

Comprehensive result X0

Optimal data

1

1

1

1

1

1

1

0.28

0.84

0.76

0.75

0.75

0.56

2

0.5

0.68

0.61

1

0.75

0.78

3

0.43

0.93

0.87

0.75

0.5

0.77

4

0.43

0.87

0.63

0.25

0.75

0.76

…

…

…

…

…

…

…

74

0.38

0.91

0.80

0.75

0.5

0.74

0.92

0.88

0.92

0.62

Upper extremity length X1

0.608

Index

Correlation

0.694

Hand length X2

0.573

Shoulder width X3

0.649

Pulmonary/ weight X4 0.912

Upper extremity stability X5

Table 5 Sniper selection index correlation degree table

0.801

Static endurance X6 0.721

Breath holding ability X7 0.826

Emotional stability X8 0.753

100 m precision shooting X9

0.843

350 m precision shooting X10

0.879

Neurological type X11

0.857

Attention X12

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shows the final results: C1 = 0.608, C2 = 0.684, C3 = 0.573, C4 = 0.649, C5 = 0.912, C6 = 0.801, C7 = 0.721, C8 = 0.826, C9 = 0.753, C10 = 0.843, C11 = 0.879 and C12 = 0.857. Thus, the influences of all indexes imposed on sniper selection are as follows: upper limb stability > nerve type > attention > 350-m precision shooting > emotional stability > static endurance > 100-m precision shooting > breath-holding ability > hand length > vital capacity/body weight > upper limb length > shoulder width.

3 Conclusion The study sufficiently drew lessons from the principle and method of the selection of sports talents and determined the model of indexes of sniper selection and assessment standards with questionnaire survey and mathematical statistics in a quantitative primarily and qualitative secondly mode in accordance with the sniper characteristics and actual mission requirements. The study analyzed the sniper mission characteristics and carried out questionnaire survey to 30 sniper coaches from a special force and the training corps of a division, preliminarily selected 12 indexes of which the important degrees were higher than 4.0, namely upper limb length, hand length, shoulder width, emotional stability, static endurance, upper limb stability, breath-holding ability vital capacity/ body weight, 100-m precision shooting, 350-m precision shooting, nerve type, and attention. Then, the study sorted the important degrees of the preliminarily selected 12 indexes with gray correlation analysis, and then selected 8 indexes which highly influence the sniper by combining with expert interviews. The 8 indexes, respectively, were emotional stability, static endurance, upper limb stability, breath-holding ability, 100-m precision shooting, 350-m precision shooting, nerve type, and attention. At last, the study used the results of gray correlation analysis to calculate out the weights of the 12 indexes for sniper selection. The study provides reliable data support for further perfecting the system of indexes of sniper selection. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Special Operations Academy of PLA. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Plaster JL (1993) The Ultimate sniper—American senior sniper training manual. Chinese People’s Armed Police Force Special Police Academy, pp 10–12 2. Yubing Y, Xianqian W (2011) Sniper basic course, vol 7. Huangshan Book Society 3. Zhennan Y (2009) Sniper and sniper rifle talk, vol 3. Police Technology

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4. Sparkes LA (2005) The evolution of snipers and their implications on the modern day battlefield, vol 5. Duty First 5. FM 23-10 (2012) Army Physical Readiness Training. U.S. Army General Headquaters, p 47 6. Hanhan H (2014) Sniper training materials, pp 78–79 7. Min Z (2010) Determination and analysis of nerve types of snipers in armed police department. J Armed Police Med Coll 2010(5) 8. Pojman1 N, Behneman1 A (2008) Characterizing the psychophysiological profile of expert and novice Marksmen. National Security Associates 9. Scholtz DC, Girard ML, Vander pool LNMA (2007) The development of a psychological screening program for sniper selection

Researches on the Eye-Movement Mode of Chinese College Students in Reading English Websites Lijun Jiang, Bingbing Huang, Zhelin Li, Zhanghong Wu and Lu Lv

Abstract In order to improve the immersion and interest of Chinese college students in English web pages reading, an eye-movement pattern inquiry experiment, which included 30 college student subjects, has been carried out in this research. A civilian eye tracker, Tobii Eye Tracker 4C, is chosen as the interactive device, the gaze time and regression are chosen as eye-movement indicators, and a set of classification models are built based on the differences of eye movements between familiar word reading and unfamiliar word reading. According to the classification models, a browser extension named Chinen Translation is developed, which can translate automatically and timely. In the usability test of Chinen, the prediction ability of the unknown words in the full text of the 30 subjects in the classification model is 96.69% for average, the highest is 99.35%, and the lowest is 93.55%.




Keywords Eye control Classification model web page reading College students





Automatic translation
English

1 Introduction The eye-tracking method is used to measure the user gaze point and the direction [1] of gaze. Ware and Mikaelian [2] found that response time of the feedback of eye-tracking method is half of the response time of tasks like giving simple choices and the traditional cursor-positioning tasks. Given the splendid efficiency of eye-tracking method in some given circumstances, the method of eye-tracking is under enormous researches, whose development is salient in both academic area and in the marketing and consumption area. The eye-tracking method is applied as L. Jiang (&)
B. Huang
Z. Li
Z. Wu
L. Lv South China University of Technology, Guangzhou, China e-mail: [email protected] L. Jiang
Z. Li Human-Computer Interaction Design and Engineering Technology Research Center, Guangzhou, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_22

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one of the vital index for measuring the reading process in psychology of linguistic and reading, referred by Guoli and Xuejun [3], etc. Chinese people have become the largest group of English learners [4]. Despite the reading researches of English reading material’s eye-tracking method is abundant, these achievements are not apposite for further pragmatic application to deal with the practical problems that people may come across in the English reading process. This research targets at Chinese undergraduate students. A civilian eye tracker is chosen as an interactive device. By discovering differences of eye movements and building the corresponding classification models, an interactive application which can anticipate the intervene time and translate automatically is developed. The objection of the application is to make college students be occupied in reading, thus improving the efficiency, immersion, and interest of reading, and some suggestions will be made for the eye-movement interaction design.

2 Eye-Movement Mode Experiment This experiment is targeted at exploring the natural eye-movement differences between college students when processing unfamiliar words and non-unfamiliar words, and building a classification model according to the differences. Meanwhile, the translation behavior of the subjects will also be recorded, and its features will be analyzed.

2.1

Subjects

We selected 34 college students at random, including 16 males and 18 females. Their ages are between 22 and 26. All the subjects have normal vision or corrected vision.

2.2

Eye-Movement Mode Data Collection System and Eye-Movement Device

The devices applied for the eye-movement data systems include the Eye Tracker 4C, a 15.6-in. laptop with a resolution of 1366  768, and a 24-in. external screen with a resolution of 1920  1200. The data processing and information flow design between devices are shown in Fig. 1. The program will be circulated in 10 ms, and the theoretical timing deviation will be ±5 ms.

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Fig. 1 Data processing and information flow design

2.3

Reading Material and Media

Three English reading materials are selected for the test. Material 1 was adapted from the reading materials of high school students. Material 2 and material 3 were adapted from the real reading questions of CET-6. All three texts are 155 words. The analysis words of materials 1, 2, and 3 accounted for 5.16, 14.19, and 13.55% of the whole paper, respectively. Another reading exercise is also provided to help the subjects get familiar with the operation. According to Chitty’s [5] guide for eye-movement interaction interface design, English web page text is displayed in the middle with the font size of 24px, line height of 76px, and font size of Arial.

2.4

Target Data

The naming and encoding values of variables collected in this experiment are shown in Table 1. In this study, multiple regression analysis was used to explore the effects of variables on gazing time. As the difficulty of words (DW) is a definite order

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Table 1 Naming and encoding values of variables Variable

Naming

Encoding value

Gazing time Difficulty of articles Word annotation Difficulty of words Word character number Number of syllables Number of correct Answers Number of unfamiliar Words Student English proficiency

– DA LW DW NCW NSW – –

Actual value (ms) 1: simple 2: difficult 1: unfamiliar 2: familiar 1: elementary 2: advanced 3: professional Actual value Actual value Actual value Actual value

SEP

Numbers of correct answers/number of unfamiliar words

variable, the word difficulty DW is transformed into two dummy variables, MDW and HDM, with the following values:
Elementary

2.5



MDW ¼ 0 MDW ¼ 1 MDW ¼ 0 Advanced Professional HDW ¼ 0 HDW ¼ 0 HDW ¼ 1

The Grading of the English Proficiency of the Subjects

As shown in Eq. (1), the way of quantifying the current English proficiency of the subjects in this research is that subjects with higher English proficiency should answer more correct reading questions; subjects with higher English proficiency should marked fewer unfamiliar words, and they should get higher English proficiency assessment scores. English proficiency ðSEP) ¼

2.6

Numbers of correct answers Numbers of unfamiliar words

ð1Þ

Experimental Result

The study collected reading data from 30 subjects, 15 men and 15 women. Since this study only focused on the reading of 51 target analysis words within three reading materials and ignored the unprocessed target analysis words, 1459 target analysis words of the regression and gaze time data were included in the experimental reading data. The experimental data also included the data collected, while the subjects were able to use the translation function. The trigger time of translation,

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the number of interpretative toggles, and the time of interpretation staring on the words were collected. In the 571 unfamiliar words, 504 of the target words were analyzed, which accounted for 88.27%.

3 Prediction and Classification Model Construction 3.1

Exploration of Word Processing Model

Zuo and Yang [6] divided the regression into six types, but this classification method is actually too subdivided that it is harmful to the accurate classification. This research defines the reader’s regression as the reading of the subsequent four words after the target word. Other cross-sentence or cross-paragraph regression is precluded in the recognition of the reading eye-movement pattern. According to the times of regression in the sentence, word processing is divided into three modes: S1 is processed once, S2 is processed twice, and S3 is processed multiple times.

3.2

Analysis of the Influencing Factors of Word Staring Time

The gazing time is set as the dependent variable, while the student English proficiency (SEP), the word character number (NCW), and word syllable number (NSW) as covariates in the SPSS 24 software. The difficulty of article (DA), difficulty of words (DW), and words annotation (LW, mark said strange words, not mark said the unfamiliar word) are set as fixed factors. By applying the general linear model (GLM) method, combining with step-by-step analysis of the main factors [7], and implementing multi-factor analysis of variance, we can come to conclusion that in S1 class words, the difficulty of articles (P = 0.000) and the word mark (P = 0.000); in S2, the difficulty of the article (P = 0.026) and the word labeling (P = 0.000); in S3 class, the difficulty of the article (P = 0.396) and the word labeling (P = 0.000). Combined with the above results and mean comparison results, we can come to the conclusion that the gazing time of unfamiliar words was significantly higher than that of similar non-unfamiliar words in the three processing modes of word reading. In the processing modes of S1 and S2, the gazing time of words in the more difficult articles is significantly higher than that of similar words in simpler articles.

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Construction and Screening of Gazing Time Prediction Model

As target analysis words in low difficulty material 1 is so few that they are precluded from quantitative analysis. Therefore, the number of remaining words for analysis is 1240. According to the general linear model method, the gazing time is set as the dependent variable, with the student English proficiency (SEP), the number of characters (NCW), and word syllable (NSW) as covariates. With the word difficulty as a fixed factor, multiple factor analysis of variance is performed, respectively, for three kinds of word processing modes in the unfamiliar words. Therefore, the variables related to the gazing time are discovered, and a mathematical model is built. The biggest multiple correlation coefficient (R) for the TS of the gazing time prediction model is selected. The results are shown in Table 2. According to the intercept value in the regression equation and the coefficient value of all relevant variables, the more accurate prediction model TS under the three modes is sorted out. The unit of the model is millisecond (ms), and the minimum value is 0. The model is shown in Eq. 2: 8 < TS1 498:75  141:98  SEP þ 17:96  CNW þ 51:32 MDW þ 67:76  HDW TS TS2 739:44  161:13  SEP þ 45:21  CNW ð2Þ : TS3 1792:21 þ 716:37  SEP

It can be seen that the ranking of influences of effect sizes of different factors on the staring time of non-unfamiliar words in class S1 in the table from large to small is English proficiency score, word character number, and word difficulty. The ranking of the factors affecting staring time of non-unfamiliar words in class S2 is differences in word character number and English level. The factors that influence the staring time of unfamiliar words in S3 are solely English proficiency scores. Subjects with higher English proficiency have relatively longer staring time during

Table 2 Prediction model of the gazing time in three word processing modes Word processing mode

Prediction model TS

R方

Related variable Variable Normalized beta value

S1

TS1 (The prediction model of the gazing time for familiar words)

0.113

S2

TS2 (The prediction model of the gazing time for familiar words)

0.123

S3

TS3 (The prediction model of the gazing time for unfamiliar words)

0.076

SEP NCW HDW MDW SEP NCW SEP

−0.258 0.165 0.113 0.103 −0.230 0.292 0.276

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repeated processing. This feature is opposite to S1 and S2, which can reflect the difference in reading processing strategies between subjects with different English proficiency.

3.4

Construction of Classification Model

It is known that the staring time of the subjects for unfamiliar words is significantly longer than that for non-unfamiliar words. The idea of constructing the classification model is shown in Eq. 3. a is constant. The values of the standard estimation error of each of the three TS models can be positive, negative, or 0. By adding different values into the process of categorization model and comparing the resulted false judgment and missing word, the optimal value a is obtained. CS ¼ TS þ a

ð3Þ

In this research, the ability of accurately predicting the proportion of unfamiliar and non-unfamiliar words among all the words analyzed by the readers is called unfamiliar word prediction ability. In S1, when the constant a is 290, CS1 is the best predictor of unfamiliar words in the target analysis word, which is 79.95%. In S2, when the constant a is 220, CS2 is the best predictor of unfamiliar words in the target analysis word, which is 76.40%. In S3, when the constant a 3 is −750, CS3 has the best prediction ability for unfamiliar words in the target analysis word, which is 84.69%. The classification model is summarized as shown in Eq. (4). The unit is millisecond, and the minimum value is 0. 8 < CS1 CS CS2 : CS3

788:73  141:98  SEP þ 17:96  CNW þ 51:32 MDW þ 67:76  HDW 959:44  161:13  SEP þ 45:21  CNW ð4Þ 1042:21 þ 716:37  SEP

The mechanism of classification model in translation is that first, judge whether the reader is currently reading the targeted word. If not, no calculation will be made. Otherwise, calculate the corresponding time points of the word in the classification models CS1, CS2, and CS3, respectively, and judge the processing mode of the word adopted by the reader. Then compare the current staring time with the time points calculated by CS in this mode in real time. If the staring time of the word exceeds the time point output of CS, the word is regarded as an unfamiliar word to the reader. The logic judgment to determine the processing mode is shown in Fig. 2. The theoretical error of this function is less than 5 ms for every 10 ms cycle. According to the above classification models, a browser extension named Chinen Translation is developed, which can translate automatically and timely, and a usability test was conducted.

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Fig. 2 Logical judgment diagram of word processing mode

The data of unread target analysis words and repeated records were excluded. Among 1290 target analysis words, a total of 251 were missed or misjudged. Among the 30 subjects, the prediction level of total unknown words was 80.54%, among which the highest was 95.35% and the lowest was 65.12%. Considering that 57 non-target analysis words labeled as unfamiliar by the subjects are part of the missing judgment, the prediction ability of the unknown words in the full text of the 30 subjects in the classification model is 96.69%. The highest was 99.35%, and the lowest was 93.55%.

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4 Conclusions According to the analysis of the translation operation of 30 subjects, the subject translated only 60.49% of the strange words. The percentage of subjects that tended to translate the words for the second or third time reading accounts for 54.92%. The subjects only read 1.21 interpretations on average, and the average reading time of each Chinese interpretation was 216.31 ms. It was found in the interview that 90.00% of the subjects believed that the form of single interpretation was better, and 60.00% of the subjects believed that the interpretation should disappear after reading, of which 43.33% believed that it should disappear automatically. 63.33% of the subjects thought that the way the original text was displayed would affect the second reading experience. The period that the amount of time a word’s cumulative staring time exceeds the predicted value of the classification model is called the pre-trigger time period. There was a significant difference in the pre-trigger time of data S1, S2, and S3 (P = 0.013). According to the median, the pre-trigger time periods of S1, S2, and S3 were 300, 200, and 500 ms. When the time of staring at a target word exceeds the upper limit of the predicted time of classification model by one pre-trigger time, the translation of the targeted word will be triggered automatically. This translation behavior makes the intervention more natural and in line with the user’s psychological model. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of School of Design, South China University of Technology. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Chen W (2008) A study of Chinese learners’ second language vocabulary acquisition. China Ocean University Press 2. Ware C, Mikaelian HH (1987) An evaluation of an eye tracker as a device for computer input2 [J]. Acm Sigchi Bulletin 17(SI):183–188 3. Yan G, Bai X, Chen X (2003) A Summary of eye movement theory in reading process. Stud Psychol Behav 1(2):156–160 4. Machine Translation system to panic translators [EB/OL]. http://mp.weixin.qq.com/s/ C5YtIdwQtb2ViQDOZC_RaQ.2018-03-15 5. Chitty N (2013) User fatigue and eye controlled technology. Stw.ryerson.ca 6. Zuo Y, Yang Z (2006) Eye tracking study of second language reading in different cultural contexts and difficulties. Psychol Sci 29(6):1346–1350 7. Bao H, Liu D, Yang P et al (2007) Stepwise screening of main influencing factors for univariate and multivariate observational data. China Health Stat 24(1):33–35

Research on the Needs of Elderly Users of Electronic Sphygmomanometer Design Nan Li and Liqing Huang

Abstract Taking electronic sphygmomanometer as the research object, the user demand attributes and importance analysis were carried out to fully excavate the needs of elderly users based on Kano model. Through literature search and card sorting, the elderly’s needs for sphygmomanometer were preliminarily classified. Kano model questionnaire was used to analyse the importance of related demand attributes of the elderly. The results showed that the elderly had lower requirements for the appearance of the product and higher requirements for product performance and comfort. Combined with the hierarchy of demand attributes, design suggestions are proposed to improve the customer satisfaction of electronic sphygmomanometer for the elderly, which has important application value for improving the product market competitiveness. Keywords User demand Sphygmomanometer


Hierarchy of needs theory
Kano model


With the coming of China’s age of ageing, the demand for products from elderly users has increased significantly. Coupled with the rapid development of the Internet industry, how to improve the degree of acceptance and adaptability of products for elderly users in such an era in which product updating is so rapid is the focus of attention at present. For the elderly people, the problem that they are most concerned about is health management. An electronic sphygmomanometer is the most common household medical product. With the characteristics of safety, convenience and accuracy, it is an indispensable medical tool for hypertensive people to detect blood pressure changes. In order to improve the elderly users’ satisfaction with electronic sphygmomanometers, this paper introduces Kano model to analyse their demand points of electronic sphygmomanometers, so as to guide the design.

N. Li (&)
L. Huang Jiangsu University, Jiangsu 212013, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_23

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1 List of Attributes of Sphygmomanometer Products Based on Card Sorting Card sorting is a method of information induction and information architecture. It is usually used to compare the differences between classification methods of interface labels and the target users’ cognition of interface information, so as to explore users’ psychological and behavioural demands [1]. The purpose of card sorting is to understand which kind that people will classify information into, the relationship between information, and how to describe the classified information. Product descriptions were obtained by referring to relevant literatures. Five elderly users who are skilled in using electronic sphygmomanometers were invited for interviews, including two males and three females, with an average age of 63-years old. Their habits and preferences of using electronic sphygmomanometers were investigated. According to the users’ scores on various demands, the product attributes of aspects such as bright colour, appearance, mechanical fault reporting, portability and strong endurance are eliminated to obtain the Level-III demand indicators for sphygmomanometers. According to the Level-III demand indicators, three students majoring in design were invited to conduct closed card sorting to obtain classifications of Level-I and Level-II demand indicators, as shown in Table 1. Table 1 Electronic sphygmomanometer equipment demand attribute list Primary demand

Secondary demand

Level-III demand

Remind function

Reference BP range Last measurement

Normal BP range Voice broadcast reminder BP graphic Tightness test Position detection LED warning Irregular pulses alert Intelligent pressure Speech recognition Voice input Single-hand wear One-key measure Automatic power-off BP memory in 90 groups Family BP memory Fluctuation trend of BP Weekly BP comparison Seasonal comparison of BP APP synchronization Low decibel High-definition screen

Wear prompt Health warning Artificial intelligence

Intelligent pressure The voice function

Interactivity

Single-hand wear One-key measure Automatic power-off Data memory function

Information communication

Data comparison function

Comfort

Data sharing Low noise High-definition screen

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2 Analysis of Demands for Electronic Sphygmomanometers Based on Kano Model 2.1

Kano Model

According to the existing product attributes, in order to rank the importance of product attributes, Kano model theory in user research is introduced. Kano Model, the theory of “Must-be Quality and Attractive Quality” put forward by famous Japanese quality management expert Noriaki Kano, is to classify customer demands according to different influences, so as to realize the research on the relationship between customer satisfaction and the degree of meeting customer demands [2]. Kano model divides user demands into six categories: must-be demand (M), one-dimensional demand (O), attractive demand (A), indifferent demand (I), reverse demand (R) and problem demand (Q). Attractive demand, one-dimensional demand and must-be demand are usually considered. Attractive demand refers to the demand that is not easily taken into account by users. When it is not satisfied, users’ satisfaction will not be affected; when it is satisfied, users’ satisfaction will be greatly enhanced. With regard to one-dimensional demand, when it is satisfied, users’ satisfaction will be enhanced; when it is not satisfied, users’ satisfaction will be reduced. Must-be demand is functions that users think sphygmomanometers must have, when it is satisfied, users’ satisfaction will not be affected; when it is not satisfied, users’ satisfaction will be greatly reduced.

2.2

Analysis of User Demands Based on Kano Model

According to Kano model theory, a questionnaire is designed by using positive and negative questions. Questions are put forward for a total of 14 secondary attributes listed in Table 1, namely how do users evaluate the sphygmomanometer if there exists such an attribute and how do users evaluate the sphygmomanometer if there doesn’t exist such an attribute? In order to avoid the users’ conventional thinking about the questionnaire, question style and question order are randomly distributed

Table 2 Kano evaluation table Customer attitude Functional

Like Must-be Neutral Live with Dislike

Dysfunctional Like Must-be

Neutral

Live with

Dislike

Q R R R R

A I I I R

A I I I R

O M M M Q

A I I I R

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in designing the questionnaire. Each question provides five options for reference: dislike, live with, neutral, must-be and like. The demand attributes are classified according to users’ evaluations obtained, and the criterion of Table 2 and the statistical result are obtained. To investigate and survey user attitude, a total of 44 questionnaires were sent out, including 28 for males and 16 for females, with an average age of 61-years old. Excluding incomplete questionnaires and noneffective questionnaires [3] of which the total number of reverse demand and problem demand is greater than 2, 40 valid questionnaires were recovered, with a recovery efficiency of 90.90%. Taking into consideration that feedbacks of the questionnaire on the life status of the elderly are incomplete and demand attributes of sphygmomanometers obtained from questionnaires are somewhat biased, 10 middle-aged and elderly persons were invited for in-depth interviews, including four females and six males, with an average age of 72-years old, so as to better understand user demands and improve the survey data. Statistics of the survey result is conducted according to formula (1)–(4) to calculate the proportion of demand categories of each attribute. The demand category with the highest proportion is the demand category of the attribute. The statistical results of user demand survey are as shown in Table 3. KMi ¼

Mi Mi þ O i þ A i þ Ii

ð1Þ

Table 3 Survey statistical results Number

Secondary demand

KM (%)

KO (%)

KA (%)

KI (%)

Kano attribute

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Reference BP range Last measurement Wear prompt Health warning Intelligent pressure The voice function Single-hand wear One-key measure Automatic power-off Data memory function Data comparison function Data sharing Low noise High-definition screen

39.13 31.91 22.22 26.09 23.91 18.60 35.56 28.89 15.79 9.09 15.91 18.60 10.26 18.18

21.74 17.02 35.56 28.26 23.91 13.95 24.44 33.33 28.95 38.64 25.00 9.30 43.59 20.45

4.35 12.77 11.11 19.57 6.52 18.60 17.78 11.11 31.58 15.91 18.18 11.63 17.95 13.64

34.78 38.30 31.11 26.09 45.65 48.84 22.22 26.67 23.68 36.36 40.91 60.47 28.21 47.73

M I O O I I M O A O I I O I

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KOi ¼

Oi Mi þ Oi þ Ai þ Ii

ð2Þ

KAi ¼

Ai Mi þ Oi þ Ai þ Ii

ð3Þ

KIi ¼

Ii Mi þ Oi þ Ai þ Ii

ð4Þ

Importance of User Demands

In order to understand the influence of each demand on user satisfaction, the customer satisfaction index (CSi) and customer dissatisfaction index (DSi) [4] are introduced. CSi indicates the influence on user satisfaction when the product has such an attribute in the product, and DSi indicates the influence on user dissatisfaction when the product does not have such an attribute. The specific calculation method is as shown in Formula (5) and (6). CSi ¼

KOi þ KAi KMi þ KOi þ KAi þ KIi

ð5Þ

DSi ¼

KMi þ KOi KMi þ KOi þ KAi þ KIi

ð6Þ

Assuming that customer satisfaction index is as important as customer dissatisfaction index, the one with higher weight between CSi and DSi is selected as the absolute weight Ti of the ith attribute; then the relative weight Wi of the attribute is obtained by normalizing the absolute weight. The calculation relationship [5–7] is as shown in Formula (7) and (8). Ti ¼ maxðCSi ; DSi Þ Ti W i ¼ Pn

i¼1

Ti

ð7Þ ð8Þ

According to Formula (5)–(8), the importance of each attribute is calculated. Then the attributes are sorted according to their weight values and integrated into the list of attribute levels.

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3 Design of Electronic Sphygmomanometer for the Elderly 3.1

Demand Positioning of Sphygmomanometer for the Elderly

As a special group, the elderly’s brain and limb reactions become dull, and the functions of their sensory organs decrease and their capability to accept external information decreases significantly compared with that in younger age due to physiological degradation. The efficiency of information transmission in their use of products shall be fully considered. At the same time, the elderly are not only prone to mentality of being upset, lonely, irritable, self-abased and depressed, but also stubborn, sensitive, anxious, and sometimes extreme, easy to be emotional. Their capability of adapting to surrounding changes also decreased [8]. Considering their psychological characteristics, products shall be more concise, easy to use and caring. According to the previous interviews, the elderly users have a low demand for the appearance attribute of the product. They do not attach great importance to the taking in and placement of the product. The main focus centres on whether the product is durable and easy to use. Product attribute demands obtained according to the questionnaire are extracted according to their importance. Top 8 attribute demands are as shown in Table 4. The must-be demands (M) of an electronic sphygmomanometer for the elderly are single-handed wearing and range of blood pressure for reference; the one-dimensional demands (O) are a one-key pressure measurement, low noise, wear prompts, health warning and data memory function; the attractive demands (A) are automatic power-off.

Table 4 Demand attribute list of electronic sphygmomanometer for the elderly Primary demand

Interactivity

Comfort Remind function

Information communication

Secondary demand Kano attribute

Ti/%

Wi/%

Important degree

One-key measure

O

62.22

8.75

1

Automatic power-off

A

60.53

8.51

4

Single-hand wear

M

60.00

8.44

5

Low noise

O

61.54

8.66

2

Reference BP range

M

60.87

8.56

3

Wear prompt

O

57.78

8.13

6

Health warning

O

54.35

7.65

8

Data memory function

O

54.55

7.67

7

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Optimum Design of Household Electronic Sphygmomanometer for the Elderly

In view of the product attributes summarized in Table 4, considering that the existing electronic sphygmomanometers on the market have a preliminary consideration on aspects such as one-button blood pressure measurement and automatic power-off, the design optimization of electronic sphygmomanometers for the elderly mainly carries out innovative design from three aspects: wearing prompt, early warning for health and cloud communication. With respect to the wearing prompt function, when the users put on the matching sleeve, the built-in range finder calculates the reflection distance between the sphygmomanometer and the metal ring of the gas filling tube of the sleeve, so as to judge whether it is worn accurately and then feedback to the display to prompt the user. With respect to early warning for health, a tooltip is set up according to the physiological characteristics of visual diminution in the elderly. The tooltip shows different colours according to different blood pressure values. When blood pressure value exceeds the normal range, the tooltip shows a bright colour. When abnormal blood pressure occurs, the data is pushed to mobile phone software at the same time to prompt family members to pay attention to it, which forms a multidimensional health care. The main function of data memory is to remember values and family blood pressure communication. It sets up the memory key to view past data and switch key to record blood pressure values of different family members. At the same time, the sphygmomanometer is connected to the mobile phone software through Bluetooth. The data of the past week or month can be queried in the mobile phone software, and the trend chart of the index change is also provided, so that users can understand the blood pressure and its changes more systematically (Fig. 1).

Fig. 1 Design of home electronic sphygmomanometer for the elderly

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4 Conclusions This study is conducted from the perspective of the demands of the elderly. By virtue of card sorting, Kano model is used to analyse the demands for household electronic sphygmomanometer. Combining interviews and questionnaires, the demands of the elderly for electronic sphygmomanometer are screened to abstract-related demands of the elderly in four aspects, namely interaction, comfort, prompting and communication. Combined with the physiological and psychological characteristics of the elderly, the design scheme put forward is further refined. The user research method adopted for the elderly is not only applicable to the study of an electronic sphygmomanometer, but also applicable to the demand exploration of other products for the elderly and can provide ideas for related studies. Acknowledgements Thanks to foundation of Jiangsu University’s scientific research project (17C625). Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Jiangsu University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Mengna X (2017) On interface design and card classification. Beauty & Times 2017(7):86–88 2. Wang T, Ji P (2010) Understanding customer needs through quantitative analysis of Kano’s model. Int J Qual Reliab Manage 27(27):173–184 3. Xiang Y, Rong H, Xi Y et al (2018) Functional hierarchy study of wearable devices for the elderly based on user demand. Pack Eng 2018(20):159–165 4. Matzler K, Hinterhuber HH (1998) How to make product development projects more successful by integrating Kano’s model of customer satisfaction into quality function deployment. Technovation 18(1):30–38 5. Jiajun S (1994) Quality function deployment. Aeronaut Standard Qual 1994(5):9–15 6. Jingya Q (2009) Research on fuzzy front-end analysis model of new product development based on QFD and Kano. Zhejiang University 7. Gang C, Jinhong S, Weiguo M et al (2016) Design method of hand—assisted micro— cultivator based on user demand analysis. Mach Des 2016(11):11–16 8. Huilan Y, Yinghai H (2016) User research in the design of home appliances for the elderly. Design 2016(9):106–107

Analysis of Syncope Problem in Single Elderly and Application of Related Monitoring Products Chen Ni

Abstract This study aims at the problem of the aging of the world’s population, the present situation of the “single elderly” group, the common diseases and symptoms of the elderly living in China, the use of sensors, etc. In order to improve both the instructions of solitary life of single elderly and their physical and mental health, product design strategy is used in this study. This paper analyzes the symptoms of common diseases and the use of sensors in the elderly population in China by investigating the existing cases and thus provides a design strategy based on sensors. In view of the behavior dynamics of the target population, the interview content is collected by applying the approach of interviewing focus group. Four key words are summarized after the oral analysis of the content, which is real-time, timely, one-touch operation and passive operation. The design is developed about these four key words in order to get a clear direction and coherence. The innovation of the final product is mainly “active operation” and “double monitoring guarantee,” which could improve the accuracy of syncope monitoring and timeliness of the indicator ultimately.




Keywords The single elderly syncope monitoring active operation Surroundings

1 Purpose of Research With the development of China’s economy, the problem of population aging is becoming more and more prominent. It is estimated that the population of the elderly above 60 years old will reach 483 million in 2050, that is to say, there will be one elderly in every three persons in 2050, accounting for one-fourth of the global elderly population at that time [1]. With the aging of the population, the corresponding pressure of provisions for the elderly is gradually increasing. One of its specific manifestations is the high proportion of the empty-nest elderly. At C. Ni (&) Dalian Institute of Science and Technology, Dalian, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_24

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present, urban and rural empty-nest families account for 50%. In some large and medium-sized cities, empty-nest families even account for more than 70%. It is estimated that the number of empty-nest elderly families will reach 56% by 2025 [2]. As people grow older, various diseases also appear and plague the elderly population. It is understood that the number of elderly patients suffering from geriatric diseases is much greater than that of other populations. In China, 13,000 people die of geriatric diseases every day on average, accounting for more than 70% of the total death toll. According to the survey, common geriatric diseases include the following: internal medicine diseases such as hypertension, hypotension, various cardiovascular and cerebrovascular diseases, anemia, hypoglycemia, etc.; nervous system lesions such as cerebral ischemia lesions, brain lesions, some types of epilepsy; ear diseases, cervical spondylosis, cerebral arteriosclerosis, heart disease, insomnia, etc. After a thorough understanding of the above diseases, it is found that most of the common diseases in the elderly today will produce syncope symptoms. Syncope is disturbance of consciousness caused by insufficient cerebral blood supply for various reasons. When syncope symptoms occur, people may faint since they cannot maintain standing posture. In severe cases, people will lose consciousness. For the elderly, the occurrence of syncope is often irregular and cannot be prevented. In light cases, the elderly are only vague in consciousness; in severe cases, the elderly may break their heads and bleed and even die. If no one takes care of the elderly, the consequences of syncope will be unbearable to contemplate! According to the survey results, the eight common causes of syncope in the elderly are as follows: psychiatric syncope, vascular syncope, bathroom syncope, hematogenous syncope, carotid sinus syncope, micturition syncope, orthostatic hypotensive syncope and idiopathic syncope [3]. The occurrence of syncope symptoms is a common and indispensable problem among the elderly. As we said above, the number of “empty-nest elderly” is increasing year by year. If no one takes care of the elderly and syncope occurs to them, the consequences will be unbearable to contemplate. For “empty-nest elderly,” when they need to be taken care of, their children are not around; when they encounter disease problems, their children are not around; even when they encounter life danger, their children cannot be timely informed, which may easily lead to tragedies. On this basis, I will design a monitoring product for syncope symptoms, so that when syncope symptoms occur, the guardians can know them timely, so as to timely take measures to ensure the life safety of the elderly.

2 Design Thinking The purpose of this study put forward under the background of the age of aging is to create a safe, comfortable and convenient life in retirement for the user with monitoring sensor technology. Based on the literatures and survey, induction and analysis of user demands, this study puts forward the design thinking of syncope monitoring products for the elderly.

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Research Object

This study is mainly to conduct humanized monitoring for syncope symptoms that may occur to the elderly population, especially the empty-nest elderly, in daily life at home. Through the analysis, research and investigation the existing literatures sorted out, a monitoring product for syncope symptoms in the elderly is designed. Its main purpose is that guardians can pay close attention to the health status of the elderly in their family in real time; guardians can be timely informed when the elderly are in danger, so as to take necessary measures as soon as possible to ensure the life safety of the elderly. The inertial sensor based on intelligent APP provides intensive care for the elderly’s daily life. It can accurately distinguish the routine activities from syncope events, adopt positioning and communication functions to timely and accurately send alarms and reminders to family members to ensure the speed of rescue, so as to minimize the harm to the elderly. The main purpose of this study includes the following aspects: 1. This study analyzed the design and cases of existing products for syncope phenomena of empty-nest elderly and conducted redesign according to the analysis results. 2. Based on the theoretical basis obtained by means of literature survey, the empty-nest elderly were interviewed and analyzed. Focus groups interviewed the elderly and wrote codes according to the interview content, so as to obtain the use requirements and design elements provided by the subjects. 3. With respect to the application design for APP interface, a concise and beautiful operation interface suitable for the elderly is designed. It also has real-time sensing, fall monitoring alarm for the elderly, comprehensive positioning, short message reminder and other functions.

2.2

Research Content

In China, the design of syncope monitoring products for empty-nest elderly is still in its infancy. Therefore, to design an APP monitoring system based on intelligent monitoring is of great practical significance. It not only has prevention and protection functions, but also can reduce the mortality rate of the elderly in emergencies. People switch from traditional human care to intelligent electronic products; people can pay close attention to the health of the elderly in real time rather than lack of care in the past; the product can immediately send SOS signal when the elderly are in danger rather than nobody knows when accidents occur; intelligent electronic products are light, portable and easy to operate; intelligent electronic products have remote function; product interaction analysis; and sensor application.

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Key Problems

The main target population of this study is the empty-nest elderly. For the syncope products, sensor settings in the intelligent products, sensors and design and study of APP for mobile phones, the designer centers on the user and meet the household demand of the elderly to the utmost extent by means of intelligent technology. The accuracy of the monitoring products for the elderly when syncope occurs; the elderly’s slow movement may be confused with syncope movements; the monitoring products will send messages to give alarms to their families through APP immediately after the occurrence of syncope. The designer shall take into account the design principles for the single elderly, such as simple principle, direct principle and emotional principle [4] when designing for special populations such as the empty-nest elderly.

2.4

Research Method

1. Participation observation method: This study investigated the elderly population to understand the problems they encounter in life due to syncope symptoms and understood the users’ actual demands by means of inquiry; understood their parents’ nursing situation and the needs for them through investigation of the people working outside; understood some emergencies the guardians encountered when caring for the elderly whenever syncope symptoms occur through investigation of geracomium and other institutions. 2. Literature research method: This study understood the key design points about market, appearance, technology and man-machine interaction by consulting materials, including network materials, market report analysis and domestic and foreign design theory books. 3. Focus Group: Focus groups are presided over by a researcher who talks to the elderly in an unstructured natural form and obtains some useful in-depth information by listening to a group of informants selected from the target market. The value of this method is that unexpected discoveries can often be made from free-discussion groups. 4. Oral analysis: Oral report analysis method is a research method based on the foundation of a series of fundamental assumptions about the process of human information processing. The content of oral report corresponds to the latest acquired information and some information in short-term memory; the information contained in memory (i.e., reportable information) is mainly basic knowledge input by operators. Generally speaking, the process of oral report analysis can be divided into three steps: segmentation, coding and statistics.

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Feasibility Analysis

1. From the trend of the aging of the social population and the symptoms of common diseases in the elderly, it is very important to design a product with the function of monitoring syncope symptoms. 2. There is a potential market scale with considerable capacity for the products of monitoring syncope of the elderly. The market is in a vacuum state, and there is no competitive product yet. 3. The elderly themselves hold an open attitude toward guardianship products. 4. The guardians (children, siblings, etc.) also have a strong demand for syncope monitoring products for the elderly. 5. Following the trend of social development, a new health model is constructed through the product—transforming from the previous concept of overdrawing health and fighting against disease to the concept of keeping healthy and preventing disease.

3 Research Process By collecting the definition of the elderly with syncope in existing literatures, cases and related products, the subjects who can participate in this interview are selected. The subjects are the elderly who have experienced syncope or their family members. Then research questions of focus group are drawn up. The designer shall give the prologue of host to make subjects participating in the interview be familiar with each other, develop the interview outline and start recording for the focus group with recording pen. The designer shall participate in the whole process, write a verbatim draft after the interview, analyze the pros and cons of the content, conduct oral analysis and extract the design elements beneficial to product development provided by the subjects.

3.1

User Analysis

3.1.1

User Portrait

To analyze from the perspective of the user, the target population was positioned to the empty-nest elderly with syncope symptoms. We divided the empty-nest elderly into three categories: the elderly without children or companion, the elderly with children but living separately from them and the elderly whose children are far away from home so that have no choice but to live alone. Five empty-nest elderly persons were interviewed face to face to mainly understand the problems that they encounter in life due to syncope symptoms and the solutions taken at that time. The user portrait compiled through the interview is as follows (Table 1).

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Table 1 Persona of user Name Age Living condition Physical condition Personal experience

Pain point

Li Jisheng 79 years old My two sons are working in other places. His wife has passed away and he lived alone all the year round I suffer from vascular sclerosis, often have dizziness and headache, relieve symptoms by taking medicine at present and have the experience of sudden syncope Once, when I got up from nap and went outside to collect the clothes I put for drying, I suddenly felt dizzy. Then I lost consciousness. I do not know how long it took. I slowly recovered. My head and hands were hurt. Now I am still very afraid when I think about it I faint suddenly every time with no one around me, so that it is very difficult to get timely treatment; in this case, I hope that my family can be around me very much

Through in-depth face-to-face interviews and desk study, we find that there are four main problems for users (the elderly): 1. In case of danger, the elderly cannot be effectively rescued in time. 2. Dangers may occur at any time of day. 3. In case of danger, the elderly may lose consciousness and cannot operate initiatively. 4. The elderly do not admit they are old, which may make them ignore the omens. To analyze from the perspective of the guardian, the target population was positioned to the guardians (children/brothers and sisters, etc.) of the empty-nest elderly with syncope symptoms. We divide guardians into two categories: those living far away from the empty-nest elderly and those living separately from the elderly in family. Five eligible guardians were interviewed face to face to mainly find out the problems their parents encountered in life due to syncope symptoms and the solutions taken at that time, their care for parents and the parents’ needs for their children. The user portrait compiled through the interview is as follows (Table 2). Through in-depth face-to-face interviews and desk study, I found that for guardians (children/brothers and sisters, etc.), there are three main problems as follows: 1. When the elderly in family are in danger, they cannot find it in time; 2. They cannot know the physical condition of the elderly in family in real time; 3. The elderly in family do not attach importance to their physical abnormalities.

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Table 2 Persona of guardian Name Age Occupation Parents Experience

Pain point

3.1.2

Shen Xiaojuan 55 years old Senior middle school teacher My mother is over eighty years old, because of bradycardia, she had sudden syncope many times My mother is usually in good health. However, she fainted at home many times in recent months. I took her to the hospital to take CT but did not find out the reason. A month ago when shopping in the street, she fainted again. We took her to the hospital in a hurry to take an electrocardiogram. It was found that her heartbeat is only 30 times per minute. It is bradycardia I am busy at work ordinarily and live separately from my parents, so that I cannot always take care of them. When they are in danger, I cannot know in time. I am very worried that accident may happen to them one day

Problem Analysis

According to the analysis of the problems existing in the user and the guardian, four entry points are put forward: real-time monitoring, remote viewing, one-key operation, active operation and accurate judgment. After finding the above four entry points, I formed a definition framework and improved it by means of building a demand pyramid (Table 3). According to the investigation, it is known that the existing products on the market need manual operation of the user. The core innovative point of the product is that once abnormal situation is detected, the product will operate actively. The specific concept is described in Table 4.

3.2

Monitoring Method

Based on the analysis of the above aspects, the product will eventually achieve the effect of double monitoring security. Next, I will elaborate on the two different core monitoring methods of the wristband and the patch, respectively. Method I: Measure the heart rate, blood pressure and blood oxygen saturation of the user (with wristband). At the early investigation stage, eight common causes of syncope in middle-aged and elderly people were summarized, including psychiatric syncope, vascular

Table 3 Product requirement analysis Real-time monitoring and positioning Remote viewing and one-key operation Active operation and accurate judgment

Demands that must be met Demands that wish to be met Unexpected surprises

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Table 4 Operation concept Daily monitoring status

Real-time monitoring of vital signs

Judgment of abnormal status

Actively prompt the user whether it needs help through voice + vibration

Heart rate Activity level Respiratory rate Blood oxygen saturation Temperature Adopt corresponding measures such as calling if there is no response within 8s Return to daily monitoring status if the user replies “no need” or press the button to close the inquiry

syncope, bathroom syncope, hematogenous syncope, carotid sinus syncope, micturition syncope, orthostatic hypotensive syncope and idiopathic syncope. Further investigation was also made on the causes of the above eight causes of syncope. It was found: Syncope was mostly accompanied by symptoms such as slow heartbeat, blood pressure drop and oxygen saturation drop [5]. Therefore, with sensors and technologies, such as optical reflective biosensor and PPG signal processing algorithm, the monitoring effect can be achieved by measuring the heart rate, blood pressure and blood oxygen saturation of the user. Method II: Measure the changes in body posture caused by gravity (with patch). Changes in body posture caused by syncope can be divided into forward syncope, backward syncope and lateral syncope. Usually, the change occurring is a process for the human body to fall down from a higher plane to a lower plane, which is bound to be accompanied by changes in the position of gravity center of human body—generally, the lowering of gravity center (Fig. 1). Traditional monitoring devices are wristbands or watches measuring changes in body posture caused by gravity with three-axis acceleration sensor; however, there are often some errors when describing changes in gravity center of human body by integrated acceleration method, which leads to frequent false alarms. Therefore, we put the sensor on the neck in the form of patch and revise the algorithm, so as to greatly improve the accuracy of measurement.

Fig. 1 Human body center of gravity position change

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Product Element Analysis

The design is carried out based on the above four entry points and the product form finally established is as follows: wristband + patch. Next, I will analyze the product from four aspects: function, man-machine, material and technology.

3.3.1

Functional Analysis

The functions of the wristband are: real-time monitoring—blood oxygen, heart rate, blood pressure; regular monitoring—sleep, activity level; passive operation; automatic positioning; remote viewing; lift the wrist brighten the screen; waterproof and dust-proof functions. The functions of the patch are: real-time monitoring—body posture changes caused by gravity; regular monitoring—body temperature; waterproof function.

3.3.2

Man-Machine Analysis

Man-machine analysis of the wristband: Insensible wearing—the frame conforms to ergonomics design, the ultra-thin frame is more comfortable, the watch strap (similar to the band tape we played with in childhood) is elastic and adheres to the wrist according to wrist size, so that it need not to be buckled firmly, which may result in blood stasis in the hands of the elderly; voice + vibration prompts— warnings and gentle vibration on wrist are specially set up to reduce the probability of missing message and prevent the user from not hearing voice prompts due to hearing problems. Man-machine analysis of the patch: Insensible wearing—in order to cooperate with the use of patching behind the ear, the equipment only weighs 11 g and is only 5 mm thick, so that it is very portable.

3.3.3

Material Analysis

Material analysis of the wristband: screen—adopting OLED display, with characteristics such as lightweight, large visible angle and significant energy saving; watch strap—adopting medical silica gel, high-grade DowCorning tpsiv soft rubber watch strap which is a special material for Apple. Material analysis of the patch: adhesive—adopting medical adhesive.

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Technical Analysis

Technical analysis of the wristband: blood oxygen saturation monitoring—adopting optical reflective biosensor. Compared with traditional sensors, reflective light interference biosensor can directly monitor the object in real time and has advantages such as high stability and sensitivity, strong anti-electromagnetic interference [6]; heart rate monitoring—adopting PPG signal processing algorithm, that is, in simple terms, to reflex and utilize the fluctuation changes of the transmittance in blood, convert them into electrical signals, and convert them through software algorithm. It corresponds to the heart rate. Technical analysis of the patch: body posture monitoring caused by gravity— adopting three-axis acceleration sensor plus barometer sensor; body temperature monitoring—adopting temperature sensor (thermistor). Technical analysis of the supporting APP: the orientation of the supporting APP of the product is to enable the guardians to not only pay attention to the health status of the elderly in family in real time, but also get timely notification and take measures when the elderly are in danger. Following the idea of being more precise, timelier and more intimate, the APP can be operated on IOS system 7.1 or above or Android system 4.4 or above. The APP has the following five core functions: displaying real-time monitoring data, including heart rate, blood pressure and blood oxygen saturation; the guardians (APP users) can timely receive messages when product users and the monitored persons are in danger; displaying regular monitoring data, including activity level, sleep duration and quality and body temperature; real-time automatic positioning; historical data records, including all real-time and regular monitoring data. It is hoped that the interaction between the wristband and the patch can achieve the function of syncope monitoring and finally play the role of caring and protecting the elderly.

4 Research Conclusions and Applications Based on sensors, this product can monitor the syncope symptoms of the elderly, especially the empty-nest elderly, and ensure the life safety of the elderly to a certain extent. Through user analysis, user demands are more clearly defined and four key words, namely real-time, timely, one-key operation and passive operation, are refined and summed up. Then design is carried out around the four key words with more clear orderliness and more clear direction. The innovative points of the final product are mainly “active operation” and “double monitoring guarantee.” With APP, in daily life, the guardians can pay close attention to the health status of the elderly in family in real time; when syncope occurs, guardians will be timely informed to take measures. Its scope of application is the elderly population with syncope symptoms. Through this product, we can strive for more precious time for the elderly who have syncope symptoms and try our best to ensure their life safety.

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The safety assurance, psychological comfort for the elderly and human resource cost savings brought by the product far exceed its investment cost. For the society with the increasing degree of population aging, the degree of demand for the product will also grow day by day with the maturity of technology.

References 1. Barer ML, Hertzman C, Miller R, Pascali MV (1992) J Health Polit Policy Law 2. Jiang XQ, Wei M (2015) Study on the health status and influencing factors of the elderly population in china. Popul J 3. Liu J, Hao X (2014) Analysis on the current situation of self-care ability of the elderly and its social support system. Health Econ China 4. Hu Q (2018) Research on intelligent product design of single elderly home care. Zhengzhou Univ Light Ind 5. Zou Q (2012) Research progress on health status of empty nesters in China. J Chuan Bei Med Coll 6. Lu Y (2009) Research status and development prospect of sensor technology. Sci Technol Inf

Physiological Measures of Mental Workload: Evidence from Empirical Studies Da Tao, Xu Zhang, Jian Cai, Haibo Tan, Xiaoyan Zhang and Tingru Zhang

Abstract Mental workload (MWL) is widely used in the design and evaluation of complex human–machine systems and can be measured by a number of physiological measures. However, the effectiveness of these measures seems unknown. This study was conducted to provide a comprehensive understanding of the effectiveness of physiological measures of MWL. Four electronic databases were systematically searched for empirical studies measuring MWL with physiological measures. Ninety-four studies were included for analysis. We identified 36 physiological measures and grouped them into electrocardiogram, eye movement, electroencephalogram, respiration, electromyogram, and skin measures. Thirty-three measures were reported to have significant associations with MWL, but their effectiveness varied. We also identified 11 physiological measures that were widely used and demonstrated high effectiveness in assessing MWL. However, their effectiveness did not remain consistent across different application domains. Our study offers insights into the understanding and selection of appropriate physiological measures to evaluate MWL in varied human–machine systems. Keywords Physiological measure


Mental workload
Human–machine system

1 Introduction Mental workload (MWL) has long been cited as an important concept in human factors and ergonomics research [1, 2] and is widely used in the design and evaluation of complex human–machine systems, such as driving systems [3] and nuclear power plants [4]. It is has gained increasing attention over the last decade, D. Tao
H. Tan
T. Zhang (&) State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, Shenzhen, China e-mail: [email protected] D. Tao
X. Zhang
J. Cai
X. Zhang
T. Zhang Institute of Human Factors and Ergonomics, Shenzhen University, Shenzhen, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_25

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as the increasing application of modern, complex technologies induces ever greater cognitive demands in varied occupational conditions [2]. MWL is a multidimensional concept in nature. In spite of a number of definitions for MWL, there is no consensus on this concept. First, workload is different from task load in that workload refers to individuals’ subjective experience in performing particular tasks under certain environments and time constraints, while task load describes external duties or amount of work that individuals have to perform [5]. Second, MWL is distinguished from physical workload in that MWL focuses more on stress caused by task demands, while physical workload focuses more on strain imposed on human body [1]. Among varied definitions, Young and Stanton provide a global one. They suggest that MWL refers to ‘the level of attentional resources required to meet both objective and subjective performance criteria, which may be mediated by task demands, external support, and past experience’ [6]. MWL could be induced by multiple factors, such as task demands, stress, fatigue, and motivation. MWL experienced under certain circumstance could differ much for different people due to individual differences in capabilities, efforts, cognition, skills, past experience, and situational awareness. MWL can be indicated by several types of measures, including subjective measures, performance measures, and physiological measures, among which physiological measures have been increasingly used in recent years due to the development of new sensor technologies. The use of physiological measures has several advantages in that data collection can be unobtrusive and would not interfere with primary tasks, the measures can be standardized and compared across different studies and scenarios, and the measures are objective evaluations, requiring a relatively small sample and providing more accurate reports of MWL [1, 5, 7, 8]. Examples include electrocardiogram (ECG), electroencephalogram (EEG), eye movement, respiration, electromyogram (EMG), and skin measures. Over the years, numerous studies have examined varied physiological measures to understand their associations with MWL for better assessing cognitive works. However, little work has been done to synthesize existing evidence to provide clear guidance for the selection of appropriate MWL measures. Jorna’s review confirmed heart rate (HR) as an effective measure for workload [9]. Marquart et al. reviewed eye-related measures of drivers’ mental workload [3]. Charles and Nixon [7], and Lean and Shan [5] conducted narrative reviews of physiological measures of MWL. However, their studies either focused only on a limited number of physiological measures [3, 9] or provided no confirmative evidence on effective measures of MWL [3, 5, 7, 9]. The purpose of this study was to systematically review existing studies on physiological measures of MWL, to summarize evidence on their effectiveness and to give guidance to the selection of appropriate physiological measures in MWL assessment in the human–machine systems.

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2 Methods 2.1

Literature Search and Study Selection

A systematic literature search was conducted in December 2018 with databases of MEDLINE, PsycINFO, PsycARTICLES, and Web of Science to identify studies that examined physiological measures of MWL. The search terms included keywords related to physiological measures (physiol* OR heart rate* OR blood pressure* OR electrocardiogram* OR electrodermal activity* OR electrodermal reaction* OR electroencephalogram* OR electrooculogram* OR event-related potential* OR breath* OR respirat* OR eye* OR skin* OR ocular* OR brain* OR blink* OR pupil* OR ERP OR EDA OR EMG), mental (cognitive OR mental), and workload (workload OR task load OR efforts). The titles and abstracts of the initial search citations were read and assessed to determine their relevance based on our inclusion and exclusion criteria. Articles considered as relevant were kept for full-text review. Reference lists of the selected articles were manually searched for additional potential articles.

2.2

Inclusion and Exclusion Criteria

Studies were included if (1) they empirically tested physiological measures using relevant technologies, devices, and sensors; (2) they quantitatively examined relationships between physiological measures and MWL; and (3) the articles were written in English and peer-reviewed. We excluded studies with no quantitative analysis on relationships between physiological measures and MWL. We also excluded review studies that did not provide original data on physiological measures of MWL.

2.3

Data Extraction and Analysis

A coding scheme was pre-constructed to guide data extraction. The information extracted included study characteristics, physiological measures, and the statistical significance of relationships between physiological measures and MWL. The effectiveness of a physiological measure was determined by majority rule. Specifically, the effectiveness of a measure was rated as high if the number of studies reporting a significant association between the measure and MWL was more than half of the total number of studies that examined the measure. Or else, it was rated as low. Two authors (DT and XZ) independently conducted article screening and selection, and data extraction. Any discrepancy was resolved through discussion and consensus.

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3 Results After a screening of 6230 initial citations and cited references of relevant articles, we identified 94 eligible studies. The reference list of the 94 studies is not provided here due to space limitation and upon request. Table 1 summarizes the characteristics of the 94 studies.

3.1

Study Characteristics

Most of the studies (55%) were conducted in the last nine years, indicating that physiological measurements were increasingly used to measure and predict MWL in recent years. Most of the studies were carried out in simulated settings

Table 1 Characteristics of the 94 studies analyzed Characteristics Year of publication Before 2001 2001–2009 2010–2018 Domain where the measures were applied Aviation Driving Nuclear power Not specified Type of participants Students Pilots Drivers Others Type of physiological measures ECG measures Eye movement measures EEG measures Respiration measures Skin measures EMG measures Studies that also employed subjective MWL measures NASA Task Load Index Subjective Workload Assessment Technique (SWAT) Other self-reported scales

N

%

17 25 52

18 27 55

36 12 4 42

39 13 4 44

31 22 7 34

33 24 7 36

67 37 24 18 5 4

71 38 24 19 5 4

38 2 39

40 2 41

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(51 studies, 54%) and were widely distributed in driving (13%), nuclear power station (4%), aviation (39%), and other domains (41%). The sample sizes of the studies ranged from 4 to 150, with a median of 16. The studies recruited a diverse range of participants, including experienced drivers (7%), students (33%), pilots (24%), and other volunteers. Electrocardiogram (ECG) measures were the mostly used measures that were tested for association with MWL (71%), followed by eye movement (38%) and electroencephalogram (EEG) measures (24%) and then by respiration (19%), electromyogram (EMG) (4%) and skin measures (5%). The studies also applied subjective measures to assess MWL, with NASA Task Load Index questionnaire (40%) being the most commonly used.

3.2

Physiological Measures of MWL

We identified 36 different physiological measures, which were grouped into six types, including ECG, EEG, EMG, eye movement, respiration, and skin measures. Table 2 shows the details of physiological measures that were reported in reviewed studies. There were 13 eye movement measures, 10 EEG measures, 9 ECG measures, 2 respiration measures, and 1 skin measure and 1 EMG measure. All the 13 eye movement measures were rated as high effectiveness, as more than half of the relevant studies reported that the measures had statistically significant associations with MWL. For ECG measures, heart rate (HR), heart rate variability (HRV), low-frequency/high-frequency ratio (LF/HF ratio), total power, SDNN, RMSSD, inter-beat interval, and PNN50 had high effectiveness as indicators of MWL. Table 2 Details of the physiological measures Type of measures

No. of measures

Details of measures

• Pupil diameter (13/9), blink rate (18/11), blink interval (3/2), blink duration (12/8), fixation duration (10/6), fixation number (2/1), blink amplitude (1/1), fixation rate (1/1), saccade rate (2/0), saccades number (2/0), saccade duration (4/1), saccade velocity (7/4), saccadic amplitude (4/2) ECG 9 • HR (44/30), HRV (37/21), heart period variability (1/0), LF/HF ratio (17/9), total power (3/1), SDNN (5/4), RMSSD (7/5), inter-beat interval (22/13), PNN50 (6/5) EEG 10 • Delta power (8/6), theta power (14/9), alpha power (14/11), beta power (15/11), gamma power (4/3), a/h (2/2), h/b (1/0), ERPs (6/6), P300 (3/3), N100 (1/1) Respiration 2 • Respiration rate (18/12), respiration amplitude (2/1) Skin 1 • Electrodermal activity (5/3) EMG 1 • Electromyogram measures (2/0) Data in parentheses indicate the number of studies reporting a significant association of the measures with MWL/ the total number of studies examining the measures Eye movement

13

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For EEG measures, delta power, theta power, alpha power, beta power, gamma power, a/h, ERPs, P300, and N100 had high effectiveness. For other types, respiration rate, respiration amplitude, and electrodermal activity were shown to have high effectiveness. Overall, HR, HRV, respiration rate, and blink rate were among the most widely used measures with high effectiveness. We also grouped the physiological measures by domains where the measures were applied. Table 3 presents the effectiveness of 12 physiological measures by domains for measures that were examined in at least ten studies. Overall, eleven of them were rated as high effectiveness, including HR, HRV, LF/HF ratio, inter-beat interval, respiration rate, pupil diameter, blink rate, blink duration, fixation duration, theta power, alpha power, and beta power. However, the effectiveness did not remain consistent across varied domains. For example, HR and HRV were shown to be effective in aviation but not in driving domain. Similarly, blink duration was an effective indicator in driving and aviation but not in nuclear power station domain.

Table 3 Effectiveness of physiological measures in assessing MWL Type of measures

Effectiveness of measures Driving Nuclear power station

Aviation

Other domains

ECG Heart rate Low Low High High Heart rate Low Low High High variability LF/HF ratio High Low High Low Inter-beat interval High NA High High Respiration Respiration rate High NA High High Eye movement Pupil diameter High Low High High Blink rate High High High Low Blink duration High Low High High Fixation duration NA High Low Low EEG Theta power NA High High High Alpha power NA High High High Beta power NA High High High NA indicates that no studies examined the measures. Due to space limitation, this includes physiological measures that were examined by at least ten studies

Overall

High High High High High High High High High High High High table only

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4 Discussion Physiological measures have been widely used to evaluate MWL in human– machine systems. However, there seems no consensus on their effectiveness. As such, the purpose of this study was to systematically review empirical studies to provide a comprehensive understanding of the effectiveness of physiological measures for MWL and to provide a general conclusion from existing knowledge. As a result of the review, various physiological measures have been observed from a total of 94 studies and their effectiveness in assessing MWL was evaluated. Our review showed that the included studies empirically tested a great variety of physiological measures that were assumed to be associated with MWL. Specially, we identified 36 physiological measures, which could be grouped into ECG, eye movement, EEG, respiration, EMG, and skin measures. It indicates that ECG, eye movement, and EEG measures were the most extensively used measures in varied application domains to assess MWL. This finding is consistent with the previous reviews [3, 5, 7]. This may be because that these measures are more sensitive to MWL and data can be easily collected with current technologies. Thirty-three measures were reported to have significant associations with MWL, indicating that physiological measures overall can be used to discriminate differences in MWL. For example, heart rate increased when there were additional task demands and memory load [10]. This was also confirmed by Jorna’s review [9]. Inter-beat interval was also shown to be sensitive to tasks with varied levels of MWL [11]. However, it should be noted that a significant association with MWL does not necessarily indicates that the physiological measure is effective in assessing MWL. In fact, many studies also reported mixed results. For instance, respiration rate was shown to be correlated with MWL in cognitive tasks in a simulated driving environment [12], while it was not sensitive to changes in workload in continuous, interactive, and control tasks [13]. To date, several reviews related to physiological measures of MWL have been published [3, 5, 7, 9]. These reviews provided a narrative review of the use of physiological measures in varied domains. However, most of the reviews provided no confirmative assessment on the effectiveness of the measures, which is of high importance for practitioners and scientists to design experiments or select the most appropriate measure. In contrast, our review proposed a simple, yet efficient method to determine the effectiveness of physiological measures by using the majority rule. We identified 11 physiological measures that were widely used and demonstrated high effectiveness in assessing MWL. It shows that heart rate, heart rate variability, blink rate, theta power, alpha power, and beta power were the mostly applied measures and they were consistently shown to be effective and reliable in MWL assessment. However, the effectiveness of the majority of the 11 physiological measures did not remain consistent across different application domains. For example, heart rate and heart rate variability were rated as high effectiveness in aviation but not in driving and nuclear power station. There was also a lack of studies examining EEG

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measures in driving domain. This may compromise the effectiveness of such physiological measures. As suggested by the previous review [7], this may be due to that the characterization and complexity of tasks in varied domains differ much and can affect the perceived MWL. It may indicate that there is no single method works well in all cases. This may also be the reason that many studies applied multiple physiological measures as well as subjective measures in MWL assessment. Future studies could choose effective measures based on these findings. This study has several limitations. First, we failed to categorize the physiological measures by characteristics of task and participants due to the lack of such information in original studies. Second, there were only a small number of studies for some measures, and their reliability cannot be fully determined. Finally, the heterogenicity of the measures and the statistical methods precluded us to qualitatively synthesize the data. Therefore, our results can only be considered preliminary. Future studies are encouraged to elaborate more of their study and provide consistent reporting of their results.

5 Conclusion This study provided a comprehensive understanding of the effectiveness of physiological measures of MWL. A number of physiological measures were applied, and some of them were widely used and had high effectiveness in assessing MWL. However, their effectiveness did not remain consistent across different application domains. Our findings have important implications for practitioners in the selection of appropriate physiological measures in MWL assessment.

References 1. Young MS, Brookhuis KA, Wickens CD, Hancock PA (2015) State of science: mental workload in ergonomics. Ergonomics 58(1):1–17 2. Galy E (2018) Consideration of several mental workload categories: perspectives for elaboration of new ergonomic recommendations concerning shiftwork AU—Galy, Edith. Theor Issues Ergonomics Sci 19(4):483–497 3. Marquart G, Cabrall C, Winter JD (2015) Review of eye-related measures of drivers’ mental workload. Procedia Manuf 3:2854–2861 4. Qin G, Yang W, Fei S, Zhizhong L, Xiaolu D (2013) Mental workload measurement for emergency operating procedures in digital nuclear power plants. Ergonomics 56(7): 1070–1085 5. Lean Y, Shan F (2012) Brief review on physiological and biochemical evaluations of human mental workload. Hum Factors Ergonomics Manuf Serv Ind 22(3):177–187 6. Young MS, Stanton NA (2005) Mental workload. In: Stanton NA, Hedge A, Brookhuis K, Salas E, Hendrick HW (eds) Handbook of human factors and ergonomics methods. Taylor & Francis, London

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7. Charles RL, Nixon J (2019) Measuring mental workload using physiological measures: a systematic review. Appl Ergonomics 74:221–232 8. Nixon J, Charles R (2017) Understanding the human performance envelope using electrophysiological measures from wearable technology. Cognit Technol Work 19(4): 655–666 9. Jorna PGAM (1992) Spectral analysis of heart rate and psychological state: a review of its validity as a workload index. Biol Psychol 34(2):237–257 10. De Rivecourt M, Kuperus MN, Post WJ, Mulder LJM (2008) Cardiovascular and eye activity measures as indices for momentary changes in mental effort during simulated flight. Ergonomics 51(9):1295–1319 11. Fairclough SH, Venables L, Tattersall A (2005) The influence of task demand and learning on the psychophysiological response. Int J Psychophysiol 56(2):171–184 12. Mehler B, Reimer B, Coughlin JF, Dusek JA (2009) Impact of incremental increases in cognitive workload on physiological arousal and performance in young adult drivers. Transp Res Record 2138(1):6–12 13. Fournier LR, Wilson GF, Swain CR (1999) Electrophysiological, behavioral, and subjective indexes of workload when performing multiple tasks: manipulations of task difficulty and training. Int J Psychophysiol 31(2):129

Ideological Method of Constructing Geometric Model of Human Heat Transfer Process Sina Dang, Hongjun Xue, Xiaoyan Zhang, Jue Qu, Chengwen Zhong and Siyu Chen

Abstract The existing models cannot simulate the heat transfer process of Chinese human body accurately. The paper focused on the geometric model of the human heat transfer process. To study the differences in the heat transfer process between Chinese and other foreign human body, the body geometric characteristics had been analyzed. Based on pilots’ anthropometric data, a geometric model of human sitting posture applied to the study of thermal environment in the cockpit was established. Besides, the thermal effect of food, the size, and location of viscera had taken into account in building the geometric model. Finally, a geometric model of the human body with ellipsoid head and ellipsoid cylinders of other parts was established. This model provides a more realistic geometric model of human heat transfer. Keywords Anthropometry


Human segment
Heat transfer
Visceral structure

1 Introduction Aircraft cockpit, cabin personnel, and microenvironment constitute a typical man-machine-environment system [1]. Cockpit is an important control platform to ensure flight safety. The comfort of the thermal environment in the cabin will influence manipulation ability of pilots, directly and determine the efficiency and health of the pilots and crew members. It is the basic requirement for creating a comfortable cockpit environment. The thermal environment in the cabin includes the heat transfer in the cockpit and human body [2]. Research on human heat transfer is the precondition of establishing comfortable cockpit thermal environment. The foundation of human heat transfer model is the human geometric model [3]. At present, the research on geometric model is based on anthropometric data from abroad, but it cannot be applied to Chinese people [4]. When the layers of human S. Dang
H. Xue (&)
X. Zhang
J. Qu
C. Zhong
S. Chen Northwestern Polytechnical University, Xi’an 710072, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_26

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tissue were established, the previous researchers did not take into account the effects of food on heat production and the heat generated by the digestive system when processing food. Therefore, the previous researchers only divided the human body into skin, fat, muscle, skeleton, and core layer and do not make a detailed division of the viscera [5]. Previous studies are simple to build geometric models. In view of the problems existing in previous models, this paper puts forward a new idea of constructing geometric models: considering the size of Chinese and the real structure of the human body; dividing the geometric model into more detailed segment; and using pilots’ anthropometric data of Chinese mixed aircraft. A human body geometric model is established which conforms to the characteristics of Chinese human body.

2 Research on Ideological Method of Geometric Model Construction 2.1

Comparison of Anthropometric Parameters Between Chinese and Foreigners

The human body should be simplified before establishing the model of human heat regulation. In this paper, the human body is simplified as an ellipsoid and ellipsoid cylinders, the head is ellipsoid, and the neck, trunk, arms, hands, thighs, legs, and feet are simplified as ellipse cylinders. The length of the ellipsoid or elliptical column in each part is defined as a segment, so the human body is simplified to 15 segments in this paper. The length of each segment is the basis of establishing a human thermal regulation system. This paper analyzes the differences in bone length between Americans and Chinese by studying the ratio of each segment to the human body and compares with several existing models. It is concluded that the existing models cannot correctly divide the segments of Chinese. In this paper, anthropometric data of Americans and Chinese with the same parameters are selected. The parameters are shown in Table 1. The data of each segment are counted and compared with the existing model, as shown in Table 2. According to the analysis of Table 2, Chinese human body data show that thighs are longer than calves, while American human body data show that calves are longer than thighs. Other model data show that thighs are shorter than calves. Therefore, in the lower limb data, the existing models are closer to the size of the Americans as shown in Fig. 1. By analyzing the relative error between the size of Table 1 Human percentiles for comparison Percentile

P1

P2

P3

P5

P50

P95

P97

P98

P99

Height Weight

161.3 52.5

162.2 54.2

162.8 55

163.9 56.5

170.8 68

178.6 84

179.6 86.5

180.1 89.4

181.5 93

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Table 2 Comparison of segmental length in Chinese, foreigners, and existing research models Body part

NASA [6, 7] (%)

Ansur1 [8] (%)

Ansur2 [9] (%)

Fiala [4] (%)

Americans (%)

Chinese (%)

Stature Head + neck Head–trunk Trunk Upper arm Lower arm Upper leg Lower leg

100.0 14.5 53.1 38.7 18.4 15.9 20.2 22.9

100.0 13.5 52.5 39 19.5 15.2 20.5 23.2

100.0 13.7 52.6 38.9 18.9 15.2 20.5 23.2

100.0 13.9 53.1 39.2 19.0 15.6 20.4 22.7

100.0 18.2 54.7 36.5 20.2 16.0 18.2 31.1

100.0 20.3 51.0 30.7 18.1 13.3 25.1 20.9

(a)

Head (American)

Head (Chinese)

(b)

0.6

0.3

0.5

0.25

0.4

0.2

0.3

0.15

0.2

0.1

0.1

0.05

Trunk (Chinese)

0

0 NASA

(c)

Trunk (American)

Ansur1

Upper arm (American)

Ansur2

NASA

Fiala

Upper arm (Chinese)

(d)

0.3

0.3

0.25

0.25

0.2

0.2

0.15

0.15

0.1

0.1

0.05

0.05 0

0 NASA

Ansur1

Ansur2

Fiala

Ansur1

Lower arm (American)

NASA

Ansur1

Ansur2

Fiala

Lower arm (Chniese)

Ansur2

Fiala

Fig. 1 Comparison of Chinese and American human body data with existing models

other segments of the two models and the existing models, we can see that these models cannot predict the size of Chinese people, so it is more urgent to find a formula to predict the size of Chinese people.

230

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Thermal Effects of Food and Simplification of Digestive System

The ideal state of human heat transfer is to supply all kinds of nutrients from food to all tissues of the body to complete the basic metabolism and exercise metabolism of the body, without consuming the body’s own tissue components, and without the accumulation of excess nutrients, so as to increase people’s weight. In this way, the nutrients absorbed by the human body can be fully utilized, and the balance of intake and expenditure can be achieved. The source of human calories is the energy released by the oxidation of nutrients in food. Food is digested by various tissues through this series of circulatory processes. As shown in Fig. 2, it is absorbed into the blood, which flows through the whole body to provide the cells with the nutrients they need, as shown in Fig. 3. Through the digestion process of food, we can know that the digestion process of food is different in viscera, so it is necessary to consider the heat effect of food and the geometric structure and location of viscera. In order to make the model more consistent with the real human body structure, the visceral distribution of human trunk is described in detail. The lung is located in the thoracic cavity of the human body, accounting for 2/5 length of the trunk, and the heart is located in the back 2/3 of the lung. The liver is located below the lung and anterior to the human body. The stomach and pancreas are located behind the liver, almost in the same segment as the liver. The kidney is below the liver and behind the human body. The large and small intestines are in the abdomen of the human body, the lower part of the human liver. There are less fat and body fluids around the viscera, and the purpose is to reduce shock and compression because the human body should be stratified, segmented and meshed. The actual human body structure is complex and cannot suit the mathematical calculation, so the human

Food

starch, fat, protein

Oral cavity Function: Grinding, tearing and degrading little of starch (final product maltose)

Colon and Rectum Function: Exhaust food without digestion and produce heat through decay.

Fig. 2 Digestive process of food

starch, fat, protein

Esophagus Function: Transport nutrients

Small intestine Function: The main place for food absorption and digestion is 90%95%. (Glucose, peptone, peptide and amino acid, fatty acid and glycerol)

starch, fat, protein

Stomach Function: hydrolyze a part of protein

Pancreas: generating enzyme into the small intestine Liver: secreting bile into the small intestine

Pulmonary ventilation

External respiration

Lung ventilation

Lung

Transport of gases in blood

Blood circulation

Intracellular oxidative metabolism

Internal respiration

Organization Ventilation

Histiocytic cells

Fig. 3 Circulation of oxygen and nutrients in the body

(a)

Digestion system

Digestion

Enter the kidney and excrete with urine

Food Excrement

Monosaccharide Amino acid Glycerol and Fatty Acids

(b)

Absorbing

Nutrition transport in the blood

Blood circulation

Provide nutrition

Intracellular oxidative metabolism

Ions, Water

+

Histiocytic cells

Monosaccharide Amino acid Glycerol and Fatty Acids

Ideological Method of Constructing Geometric Model … 231

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Fig. 4 Geometric model of the human body

viscera are simplified by human anatomy knowledge. The thermal effect of food [10] in each viscus can be calculated by Formula 1.  Mbði;1j Þ;spa ¼

0:1Mbði;1j Þ;0 t 0:0167Mbði;1j Þ;0 t þ 0:1167Mbði;1j Þ;0

t\1 h t\1 h

ð1Þ

3 Result By using pilots’ anthropometric data of mixed aircraft to establish the external dimensions of the human body, according to the digestive process of food, the thermal effect of various organs, and the application of anatomical knowledge, the real Chinese human body structure can be simplified. The head can be simplified to ellipsoid, the trunk and arms, legs, hands, and feet can be simplified to ellipse columns. The position and structure of the viscera are simplified into regular shapes according to the knowledge of anatomy. Finally, the geometric model of the human body can be built as shown in Fig. 4.

4 Conclusion Based on the analysis of anthropometric data at home and abroad, this paper compares the differences between Chinese, American, and current models and concluded that the existing models were not suitable for Chinese human body structure. It is necessary to establish a human body geometric model suitable for

Ideological Method of Constructing Geometric Model …

233

Chinese. Through the analysis of human geometric characteristics, the human body is divided into 18 segments and five layers, and the core layer is differentiated in detail. The viscera are taken into account in the geometric model. Finally, a geometric model of the human body with ellipsoid head and ellipsoid cylinders of other parts was established. This model provides a more realistic geometric model of human heat transfer.

References 1. Xiangdong X, Chunxin Y, Xiugan Y (1994) Engineering model of thermal characteristics of pilot-cockpit system and its application. Space Med Med Eng 1:22–27 2. Lu A (2014) Numerical simulation and optimization of airflow distribution in rapid cooling process of large passenger aircraft cockpit. Tianjin Univ, Tianjin 3. Lai D, Chen Q (2016) A two-dimensional model for calculating heat transfer in the human body in a transient and non-uniform thermal environment. Energy Buildings 118:114–122 4. Fiala D, Lomas KJ, Stohrer M (1999) A computer model of human thermoregulation for a wide range of environmental conditions: the passive system. J Appl Physiol 87(5):1957–1972 5. Ferreira MS, Yanagihara JI (2009) A transient three-dimensional heat transfer model of the human body. Int J Heat Mass Tran 36(7):718–724 6. NASA (1978) In: Webb Associates (eds) Anthropometric source book, vol I: a handbook of anthropometric data. Athropol Research Project Staff, NASA Reference Publication 1024, N79-11734, Yellow Springs, Ohio 7. NASA (1978) In: Webb Associates (eds) Anthropometric source book, vol II: anthropometry for designers. Athropol Research Project, NASA Reference Publication 1024, Yellow Springs, Ohio 8. Gordon CC, Churchill T, Clauser CE et al (1989) Anthropometric survey of US army personnel: methods and summary statistics. Technical report Nattick/TR-89/044, Yellow Springs, Ohio 9. Paquette S, Gordon C, Bradtmiller B (2009) Anthropometric survey (ANSUR) II pilot study: methods and summary statistics. Technical report NATICK/TR-09/014. YellowSprings, Ohio, pp 1–88 10. Sina D, Hongjun X, Xiaoyan Z (2018) Three-dimensional human thermoregulation model based on pulsatile blood flow and heating mechanism. Chin Phys B 27(11):114402-1– 114402-11

Study of Correlation Between Subjective Symptoms and Ergonomic Load Index of Automobile Assembly Workers Deshan Yin, Xiaofei Zhang, Yi Zhao and Shulin Zhou

Abstract For studying the effect of work-related ergonomic risk factors on automobile assembly workers’ health, the author investigated subjective symptoms, work management, work space, and work environment with environmental measurement and questionnaire. The Mann–Whitney U test and multivariate logistic regression were used to analyze the correlation between subjective symptoms and ergonomic risk factors. Results: The rank of incidence of six subjective symptoms is irritability, dizziness, insomnia, tinnitus, headache, chest tightness, and founding that those are statistically significant with work system satisfaction, work space satisfaction, and environmental satisfaction (P < 0.05). The occurrence of subjective symptoms is related to the work-related ergonomic load level (OR > 1). The height of the operation, the position of the equipment, and the air circulation are the main risk factors for the spontaneous symptoms. Conclusion: The incidence rate of assembly workers’ subjective symptoms is higher, which is related to the working system, work space, and work environment and is not relevant to the work training system.




Keywords Work-related ergonomic load Subjective symptoms agement Work space Work environment








Work man-

1 Preface Indicated by the existing domestic research, the identification and assessment technology of the ergonomics injury factors is still at the early stage and basically limited in on-site epidemiological investigation and injury mechanism research [1]. D. Yin (&)
S. Zhou China Academy of Safety Science & Technology, Beijing, China e-mail: [email protected] X. Zhang University of Science & Technology, Beijing, China Y. Zhao Beijing Institute of Petrochemical Technology, Beijing, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_27

235

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D. Yin et al.

There are not adequate systematic ergonomics technical researches which comprehensively consider the influences of the factors such as the labor psychology, social psychology, biomechanics, industrial design, and work environment on the man–machine interface and man–environment interface [2, 3]. Modern ergonomics, organically integrates all relevant discipline theories [4], makes machinery, equipment, tools, and site be designed more applicable for the workers’ psychological and physical features and operation requirements by revealing the correlation rules among man, machine, so environment, and the ergonomics design ensures the optimal overall performance of the man–machine–environment system, minimizes the risks of accidents and injuries, and reduces the injury, death, and loss caused by work [5, 6]. The article adopted the on-site investigation method and researched the ergonomics load index and subjective symptoms of the workers of an automobile assembly workshop by the measurement of environmental parameters and questionnaire [7].

2 Object and Method 2.1

Respondents

We randomly sampled an assembly workshop and distributed 200 questionnaires, wherein, 179 questionnaires from 168 men and 11 women of 20–58 years old (32.33 ± 9.430 years old in average) were taken back (recovery percent: 89.5%). Their work types included vehicle electrician, interior decoration, wiring under the vehicle, and alighting adjustment [8].

2.2

Content and Method of Investigation

The questionnaire investigation included the contents of man, machine, environment, and management, wherein, the content of man included satisfaction assessment and subjective symptoms; the content of machine included comfort of work space, comfort of worktable height, convenience, and flexibility of manual equipment operation, convenience of equipment placement positions, and convenience of element placement [9]; the content of environment included noise feeling, illumination feeling, temperature feeling, and air circulation; and the content of management included time of fatigue, time of intensive concentration, work pressure, physical condition after getting off work and mental state after having holidays by turns. Environmental measurement: sound level meter, illuminometer, and temperature and humidity measuring instruments were, respectively, used for measuring and recording the noise, illumination, temperature, and humidity in the

Study of Correlation Between Subjective Symptoms …

237

assembly workshop. Management personnel communication: communicated with the management personnel and workers to get further information on the assembly workshop. SPSS19.0 was used to establish the database during data analysis, and statistical analysis was carried out by using correlation analysis, variance test, Mann–Whitney U test, and logistic regression.

3 Result 3.1

Environmental Measurement

The environmental parameters of an assembly workshop, which were measured in summer, are as shown in Table 1.

3.2

Occurrence of Subjective Symptoms

Subjective symptoms are the investigated personnel’s subjective sensations to their symptoms. The investigation included the six subjective sensations of tinnitus, restlessness, headache, dizziness, chest tightness, and insomnia and dreaminess. The investigation results indicated the incidence rates of different subjective symptoms from high to low as follows: restlessness (42.2%), dizziness (36.4%), insomnia and dreaminess (33.8%), tinnitus (33.4%), headache (33.1%), and chest tightness (29.9%).

3.3

Difference Analysis Between Subjective Symptoms and Ergonomics Load Factors

Mann–Whitney U test analysis was carried out to the subjective symptoms and all satisfactions and indicated the following: training satisfaction had no statistical

Table 1 Result of environmental measurement Variable

Mean

SD

Range

Noise (dB) Illuminance (l) Temperature (°C) Humidity (%) Illuminance of the post of in-vehicle wiring (l) Illuminance of joint installation post (l)

71.99 98.36 28.26 72.71 49.20 27.70

±7.98 ±78.36 ±0.11 ±1.74 ±6.67 ±0.44

61.0–88.5 27.4–340.0 28.1–28.4 70.9–76.5 30.0–60.0 27.4–28.2

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D. Yin et al.

significance to dizziness and chest tightness, work space and equipment satisfaction had no statistical significance to insomnia and dreaminess; and the other satisfactions all had statistical significance to the six subjective symptoms, as shown in Table 2. Mann–Whitney U test analysis was carried out to the subjective symptoms and possible ergonomics load factors and indicated the following: the ergonomics load factors which influence the subjective symptoms included: time of intensive concentration, work pressure, physical condition after getting off work and mental state after having holidays by turns, comfort of work space, comfort of worktable height, comfort of seat, convenience and flexibility of manual equipment operation, convenience of element placement, noise feeling, illumination feeling, temperature feeling, and air circulation, as shown in Table 3.

3.4

Logic Regression Analysis of Subjective Symptoms

Based on the incidence rates from high to low of the six subjective symptoms, the first four typical subjective symptoms, i.e., restless, dizziness, insomnia and dreaminess, and tinnitus used are the dependent variables according to whether they exist (exist = 1, not exist = 0), and the ergonomics load levels and relevant influence factors above are used as independent variables (Table 4 is the assignment table). Table 5 shows the significant influences of the ergonomics load factors imposed on the occurrence of the subjective symptoms, which were analyzed by the two classification logistic regression models. The results indicated the influence factors for restless entering the model are, respectively, as follows according to the Table 2 Difference analysis of satisfaction and subjective symptoms Tinnitus

Restlessness

Headache

Dizziness

Chest tightness

Insomnia and dreaminess

Z P

−3.321 0.001

−4.369 0.000

−4.337 0.000

−3.624 0.000

−4.978 0.000

−2.747 0.006

Z P Z P

−2.499 0.012 −3.780 0.000

−2.427 0.015 −5.460 0.000

−3.245 0.001 −3.812 0.000

–

–

−2.889 0.004

−3.368 0.001

−2.177 0.030 –

Z P

−4.834 0.000

−4.767 0.000

−4.460 0.003

−2.975 0.000

−4.428 0.000

−2.967 0.003

Z −2.942 −5.104 −4.463 −4.021 −4.623 P 0.003 0.000 0.000 0.000 0.000 Note ‘–’: There is no statistical significance between the two (P  0.05)

−3.792 0.000

Work organization satisfaction Training satisfaction Work space and equipment satisfaction Job environment satisfaction Overall satisfaction

Work space

Work management

Component location convenience

Convenience of equipment placement

Convenience and flexibility of manual equipment operation

Worktable height comfort

Comfort of work space

Mental state after having holidays

Physical condition after getting off work

Work pressure

Time of intensive concentration

Z P Z P Z P Z P Z P Z P Z P Z P Z P

−2.037 0.042 – −3.440 0.001 −2.035 0.042 −2.369 0.018 −3.257 0.001 −2.176 0.030 −2.690 0.007 −2.033 0.042

–

–

−2.466 0.014 −3.722 0.000 −2.070 0.038

–

–

–

–

Restlessness

Tinnitus

Table 3 Difference analysis of ergonomics load factors and subjective symptom

−3.560 0.000 −2.762 0.006 −2.448 0.014 −3.206 0.001 −3.381 0.001 −3.105 0.002 −3.030 0.002

–

–

Headache

−2.100 0.036 −3.291 0.001 −2.861 0.004 −2.490 0.013

–

−3.511 0.000 –

–

–

Dizziness −2.106 0.035 −2.846 0.004 −4.601 0.000 −3.627 0.000 −2.065 0.039 −3.655 0.000 −3.721 0.000 −3.077 0.002 −2.800 0.005

Chest tightness

–

–

−2.701 0.007 −4.417 0.000 –

−2.889 0.004 −3.319 0.001 –

–

(continued)

Insomnia and dreaminess

Study of Correlation Between Subjective Symptoms … 239

Tinnitus

Environment

Noise feeling

Z −4.450 P 0.000 Illumination feeling Z – P Temperature feeling Z – P Air circulation Z −3.680 P 0.000 Note ‘–’: There is no statistical significance between the two (P  0.05)

Table 3 (continued)

−2.649 0.008 −3.927 0.000 −4.352 0.000

–

Restlessness

−4.527 0.000

–

−3.686 0.000 –

Headache

−2.742 0.006 −3.705 0.000

–

–

Dizziness

−2.924 0.003

–

–

–

Chest tightness

−2.784 0.005

–

–

–

Insomnia and dreaminess

240 D. Yin et al.

Study of Correlation Between Subjective Symptoms …

241

Table 4 Selected ergonomics load factors in logistic regression analysis and assignment No.

Factor

Assignment

1 2

High concentration of time Work pressure

3 4

Physical condition after getting off work Mental state after having holidays

5

Comfort of work space

6

Worktable height comfort

7 8

Convenience and flexibility of manual equipment operation Convenience of equipment placement

9

Component location convenience

10

Noise feeling

11

Illumination feeling

12

Temperature feeling

13

Air circulation

8 h = 4 Null = 1, little = 2, general = 3, bigger = 4, very big = 5 Not tired = 1, a bit tired = 2, tired = 3, more tired = 4, very tired = 5 Very good = 1, good = 2, general = 3, poor = 4, very poor = 5 Very comfortable = 1, comfortable = 2, general = 3, uncomfortable = 4 Very comfortable = 1, comfortable = 2, general = 3, uncomfortable = 4 Very comfortable = 1, comfortable = 2, general = 3, uncomfortable = 4 Very comfortable = 1, comfortable = 2, general = 3, uncomfortable = 4 Very comfortable = 1, comfortable = 2, general = 3, uncomfortable = 4 No feeling = 1, acceptable = 2, bad = 3, very bad = 4 Comfortable = 1, uncomfortable = 2, very uncomfortable = 3 Comfortable = 1, uncomfortable = 2, very uncomfortable = 3 Very good = 1, good = 2, general = 3, bad = 4, very bad = 5

OR values from high to low: comfort of worktable height (OR = 3.172), convenience of equipment placement position (OR − 3.062), comfortable of temperature (OR = 2.1417) and air circulation (OR = 2.127); for dizziness, it is air circulation (OR = 1.994); for insomnia and dreaminess, they are comfort of worktable height (OR = 4.276) and air circulation (OR = 1.586); and for tinnitus, they are convenience of equipment placement position (OR = 3.360), air circulation (OR = 2.147), and noise feeling (OR = 2.118), as shown in Table 5.

4 Discussion Whether the noise, temperature, humidity, and illumination in the work environment met the national requirements was judged by comparing their measurement values with the occupational exposure limits. Test results of the environmental factors indicated that both of the noise and humidity met the national standards, and the illuminance of the post for assembling electromechanical instruments

#

#

#

#

1.178– 7.962

* 1.201– 8.378 *

*

*

#

*

95% CI

#

*

#

*

#

*

*

#

*

*

*

#

#

*

*

#

#

*

#

#

Dizziness b OR

Illumination feeling Temperature feeling

* 0.883

* 2.417

# # * 1.015– * * 5.754 Air circulation 0.755 2.127 1.198– 0.690 1.994 3.776 Note *No entry variable; #non-symptom independent variable; entry condition is P

#

#

* 3.172

* 1.154

3.062

*

*

1.119

*

*

*

#

#

*

*

*

Time of intensive concentration Work pressure Physical condition after getting off work Mental state after having holidays Comfort of work space Worktable height comfort

Lightweight and Flexible of manual operation device Convenience of equipment placement Component location convenience Noise feeling

Restlessness b OR

Factor

1.203– 3.306 < 0.05

*

#

#

*

*

*

*

#

#

*

#

#

95% CI

#

#

1.586

#

0.461

# #

#

#

#

#

#

#

#

* 4.276

#

* *

#

* 1.453

#

* *

#

Insomnia b OR

Table 5 Logistic regression analysis result of subjective symptom and its ergonomics load factors

1.010– 2.490

#

#

#

#

#

#

* 1.593– 11.477

#

* *

#

95% CI

0.764

#

#

0.750

*

1.212

2.147

#

#

2.118

*

3.360

*

#

#

*

#

#

#

#

#

#

#

#

#

#

Tinnitus b OR

1.330– 3.466

#

#

1.273– 3.524

1.283– 8.798 *

*

#

#

#

#

#

#

95% CI

242 D. Yin et al.

Study of Correlation Between Subjective Symptoms …

243

(big piece work) didn’t meet the national standards. The investigation found that the assembly workshop used the natural light at daytime, and the overall illuminance was low, which was consistent with the problem reported by the workers that the work was influenced by inadequate illuminance. The management personnel explained some individual precision posts were provided with headlamps, but the on-site investigation found that none of the workers wore the headlamp because of inconvenience or discomfort, etc. Thus, it shall improve the overall illuminance of the assembly workshop by combining with artificial illumination and reinforce the training and supervision to make employees realize it is important and necessary to wear the headlamps. The Mann–Whitney U test analysis research results indicated the main ergonomics load factors which influence the subjective symptoms include time of intensive concentration, work pressure, physical condition after getting off work, mental state after having holidays by turns, comfort of work space, comfort of worktable height, comfort of seat, convenience and flexibility of manual equipment operation, convenience of element placement, noise feeling, illumination feeling, comfort of temperature, and air circulation. There are many relevant influence factors of the subjective symptoms. For measuring the influences of these mixed factors, the variables of P < 0.05 in the Mann–Whitney U test analysis were fitted into the logistic regression analysis at the same time, and the multi-factor logistic prediction models of restless, dizziness, insomnia and dreaminess, and tinnitus were, respectively, established. The results indicated air circulation was introduced into the logistic regression analysis models of the four typical subjective symptoms, and all OR values were higher than 1, which means as the dangerous factor, air circulation is closely linked with all body parties of the workers. It shall pay attention to workshop ventilation and ensure good air circulation. For the ergonomics load factors of the work space, the comfort of worktable height was introduced into the restless and insomnia and dreaminess models, and the convenience of equipment placement position was introduced into the restless and tinnitus models. The above indicates the work space of the assembly workshop was not adequately well set and shall be improved in order to prevent workers from being physically or psychologically injured. Although compared with the other ergonomics factors, the work management system did not significantly influence the subjective symptoms in the logistic multi-factor regression, the Mann–Whitney U test analysis results showed all work management ergonomics load factors in the investigation influenced the occurrence of the subjective symptom to a certain extent; thus, the enterprise shall make a more proper work management system so as to more comprehensively guarantee the workers’ health.

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5 Conclusion and Expectation The typical assembly workshop workers have a high incidence rate of subjective symptom, which is relevant to the work organization system, work space, and work environment but not relevant to the work training system. It shall improve relevant ergonomics load factors so as to protect the assembly workers’ physical and psychological health and improve their career life quality. The research investigated on present situation and did not set the control group, which may influence the result extrapolation to a certain extent and will be improved in the research of next period. Acknowledgements This study was supported by the National Key R&D Program of China, Grant No. 2016YFC0801700. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of China Academy of Safety Science and Technology. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Yuzhen L, Li Y, Gang L, Ruli Q (2015) Correlation between musculoskeletal disorders and ergonomic load levels among automobile assembly workers. J Environ Occup Med 32(5): 393–397 2. Guoxun J, Pengfei L et al (2017) Experimental study on the influence of coal mine noise on people’s attention. J Safety Sci Technol 13(10):164–168 3. Mohamed S (2002) Thermal environment effects on construction worker’s productivity. Work Study 51(6):297–302 4. Guangpeng Z (2008) Principle and application of ergonomics. China Mach Press, Beijing 5. Shulun L, Shuai Q, Shuhong L et al (2013) Human-environment system model and efficiency influence in coal mine. China Mining Mag 22(7):104–110 6. Haiyang Q, Qinjuan G et al (2015) Occupational ergonomics evaluation of a papermaking chemicals enterprise in Zhenjiang City. Occup Health 31(22):3053–3057 7. Muzammil M, Ahmad S et al (2011) Design of a workstation and its evaluation under the influence of noise and illumination for an assembly task. Work 39:3–14 8. Yan X, Manman G, Jiao W et al (2012) Investigation of occupational hazards of ultraviolet radiation and protective measures for workers in electric welding. J Peking Univ (Health Sci) 44(3):448–453 9. Wanying Y, Fuchang Z (2011) Comfort design of office chair based on ergonomics. Pack Eng 32(04):44–46

Research on the Machine Character

Lane Detection Algorithm Based on Inverse Perspective Mapping Dong Chen, Zonghao Tian and Xiaolong Zhang

Abstract The lane detection and recognition is very important in unmanned driving technology. In order to improve the accuracy and robustness of lane detection and overcome the influence of changes in illumination, curvature, and road interference, a lane detection algorithm based on reverse perspective mapping is established. The binarization image of a lane with less noise is obtained by the global optimal threshold method. Then through the reverse perspective mapping, the binary lane image was converted into the top view to overcome the shortcomings of different resolution and geometric deformation of the image caused by the perspective effect. Then, the lane images transformed by reverse perspective were clustered and fitted by k-mean algorithm, and the clear lane detection results were obtained. Finally, by analyzing the lane detection of road images under different imaging conditions, the robustness of the lane detection algorithm under the conditions of high curvature, large change in brightness, and multiple interference factors were verified. Keywords Inverse perspective mapping K-means


Lane detection
Image binarization


1 Introduction It is very important to test the motor vehicle road and segmentation in the study of intelligent traffic lights based on machine vision [1]. In intelligent traffic system, the motor vehicle detection and segmentation are not completed by manual calibration because once the camera is displaced due to wind, striking, or other external force, which would have been a failure. The deviation of detection not only can lead to

D. Chen
Z. Tian
X. Zhang (&) Army Academy of Artillery and Air Defense, Hefei 230031, Anhui, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_28

247

248 Fig. 1 Lane-line detection algorithm process based on inverse perspective transformation

D. Chen et al. Image

lane line

Binarization

K-means

extract contour Inverse perspective transformation

traffic congestion, and may lead to traffic accidents, endanger the life safety of the driver. Therefore, it is worthy of further study to analyze the lane-line automatic calibration. At present, the lane-line detection method is divided into two methods: feature [2, 3] and model [4–6]. Among them, the method based on feature determines the position of the lane by several low-level features of load. This approach requires the lane line must be painted out, otherwise, it will fail. Obviously, this method is very efficient for large urban main roads, but for sub-critical sections, it is not timely. It should also be noted that this method is not subject to detailed constraints on the features of the detected lines, so it is susceptible to noise or shelter. And, the other method is based on road model, which extracts the lane-line-related features of image information, narrowing the scope of the detection. So, this algorithm based on model is more robust and more suitable for popularization in driverless technology. To this end, the article puts forward a kind of the lane-line detection algorithm based on inverse perspective transformation and converts camera video image to a vertical view to detect the lane line. This method can take advantage of the real road model, such as lane length, right, and road conditions, and so on. Its algorithm process is shown in Fig. 1.

2 Image Binarization In the image binarization processing, the threshold method is easy to implement, and the performance and complexity of the algorithm are acceptable [7]. At present, the main method of the threshold includes bimodal method, p parameters, maximum entropy threshold method, and Otsu [8, 9]. In the bimodal and p-parameter method, the threshold T is a single value, and these are no feasibility in more complex conditions and do not apply in the process of binarization. Maximum entropy threshold method does not need a priori data, but the performance is slightly lower, so it also cannot apply to intersection video image processing. By comparison, the performance of Otsu algorithm is most suitable for the development of this system. Since the grayscale range of the intersection video image is subject to large fluctuations due to climate, sunshine, and smoke, the single threshold proposed by the Otsu algorithm is not completely suitable for this application. To this end, this

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paper proposes a global optimal threshold algorithm, which uses an integer to divide the gray value into two groups and binarize the image. In the process of the lane-line detection, it cuts out the portion of the image of the sky to reduce the problem that the edge and distance image is not clear, and the road for the most part of the image after the cut of image. Considering the sensitivity of lane segmentation to noise and speed, an image based on global optimal threshold method is used for binarization. Assume that the gray level of a picture is divided into 1 * m, ni is the i gray level, so the total number N of the picture is: m X

N¼

ni

ð2:1Þ

i¼1

The probability of the i gray value of pixels is: Pi ¼

ni N

ð2:2Þ

Then, the pixels are divided into C0 and C1 two groups with an integer K: C0 ¼ f0; 1; 2; . . .; Kg C1 ¼ fK þ 1; K þ 2; . . .; mg

ð2:3Þ

The sum probability w0 of the pixels appearing in the group of C0: w0 ¼

K X

Pj ¼ wðKÞ

ð2:4Þ

j¼1

The average u0 in the group of C0 is: PK

j¼1

u0 ¼

j  Pj

w0

ð2:5Þ

And, the sum probability w1 and the average u1 of the pixels appearing in the group of C1: m X

w1 ¼

Pj ¼ 1  wðKÞ

ð2:6Þ

j¼K þ 1

Pm u1 ¼

j¼K þ 1

w1

j  Pj

¼

1  uðKÞ 1  wðKÞ

ð2:7Þ

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Fig. 2 Binarization image of the lane line

u is the overall average of saturation of the image: u¼

m X

i  Pi ¼ w0 u0 þ w1 u1

ð2:8Þ

i¼1

The variance r2 of the two groups is: r2 ðkÞ ¼ w0 ðu0  uÞ2 þ w1 ðu1  uÞ2

ð2:9Þ

Finding the k value which is in 1; 2; . . .; m and makes the variance the largest as K, the optimal threshold. The results of image binarization are shown in Fig. 2. Among them, b is the binary image of Otsu algorithm and c is the result based on the algorithm put forward in this paper; it shows that our algorithm is significantly less noise.

3 Inverse Perspective Transformation [10, 11] Under normal circumstances, there is an acute angle between the overhead view and the horizontal line, and the amount of information contained in one pixel at different positions is not the same in a top-view image. The objects in the image are transformed from two-dimensional coordinate system into the three-dimensional world coordinate system by the inverse perspective transformation. During the conversion process, the specific position of the pixel in the original coordinate system is obtained in the world coordinate system on the basis of the correspondence relationship of four coordinate systems, and the problem that the number of the feature points is different when the same target and the camera distance are different by the perspective is overcome. Figure 3 shows the process of the lane-line projection model.

Lane Detection Algorithm Based on Inverse Perspective Mapping Fig. 3 Lane-line projection model

251

Image camera

According to the center of the projection rule: 2 3 2 3 u f x 0 u0 0  R s4 v 5 ¼ 4 0 f y v 0 0 5 T 0 1 0 0 1 0

2 3  xw 7 t 6 6 yw 7 ¼ M1 M2 Xw ¼ MXw 4 1 zw 5 1

ð3:1Þ

where ðu; vÞ are the image coordinates, Xw is the reference coordinate, and s is the scaling factor. Assuming that the road is absolutely horizontal, the value s is fixed and M is a transformation matrix that can be calculated from image calibration. So, the calculation of the inverse perspective transformation matrix is converted into a solution to the formula Ax ¼ b, which can be easily solved by singular value decomposition. Figure 4 shows the inverse perspective transformation after binary image.

Fig. 4 Lane-line detection based on inverse perspective transformation

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4 K-Means Clustering [12, 13] There are n samples X ¼ fx1 ; x2 ; . . .; xn g in the fuzzy time series and divided them into K sets u1 ; u2 ; . . .; uK based on the similarity between the sample data. The clustering center is c1 ; c2 ; . . .; cK and meets the following three properties: 1. uk 6¼ / k ¼ 1; 2; . . .; K 2. ui \ uj ¼ / i; j ¼ 1; 2; . . .; K and i 6¼ j S 3. X ¼ Kk¼1 uk k ¼ 1; 2; . . .K At first, randomly selecting K data from the sample as the initial clustering center c1 ; c2 ; . . .; cK ; then, using Euclidean distance dðxi ; ck Þ to depict the similarity between the sample data. The last assigning every sample data to a different set in accordance with the formula (4.2), which is the smallest distance, including: dðxi ; ck Þ ¼ kxi  ck k i ¼ 1; 2; . . .; n; k ¼ 1; 2; . . .; K

ð4:1Þ ð4:2Þ

Thus, the distance of each sets uk is Jðuk ; ck Þ: Jðuk ; ck Þ ¼

mk X

dðxj ; ck Þ

ð4:3Þ

j¼1

where mk is the sample numbers of the set uk , xj is the data of the set uk . The total distance between classes is Jðu; cÞ: Jðu; cÞ ¼

mk K X X

dðxj ; ck Þ

ð4:4Þ

k¼1 j¼1

where mk is the sample numbers of the set uk , xj is the data of the set uk . To readjust the clustering center cek : cek ¼

mk 1 X xj mk j¼1

ð4:5Þ

where mk is the sample numbers of the set uk , xj is the data of the set uk . If the clustering center is the same ( cek ¼ ck ) and the total distance between classes Jðu; cÞ is the smallest, we obtained the optimal clustering results, otherwise, readjusting the clustering center. In order to verify the effect of K-means clustering on the image after inverse perspective transformation, a binarized lane-line image is given after inverse perspective transformation under relatively ideal conditions. Among them, the point of discontinuity of Fig. 5a is the discontinuous lane line. In order to divide the lane,

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Fig. 5 Lane-line detection results based on K-means

we need to fit the data in the image. Figure 5b shows the segmentation after K-means clustering.

5 Experiment In order to verify the effectiveness of the algorithm, we install the small camera on the roof of the family car for image acquisition and take the real-shot road image which is high curvature, brightness, rugged, and other noise as the experimental image to test. The experimental results are as follows: Figure 6a shows lane-line detection for high-curvature lanes. It can be seen that the curved lane line after fitting is completely fitted, but the curvature of the lane line slightly changes due to the inverse perspective transformation. Figure 6b shows the road is flat or not has no significant effect on the clustering results.

Fig. 6 Lane detection of high curvature and rugged road

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Fig. 7 Lane detection of brightness and other noise road

Figure 7a shows lane-line detection for apparent brightness changes bigger. It can be seen that the K-means clustering algorithm achieves a better effect in the part where the lane line is more obvious, but the far lane is not well fitted due to the accuracy of the binarized image decreases after the gradation changes. Figure 7b shows lane-line detection for many interfering elements. It can be seen that the diamond mark in the middle of the road is filtered out by K-means clustering because the data has a similar spatial form.

6 Conclusion This paper analyzes the research status of lane-line detection in autonomous driving technology and proposes a lane-line detection algorithm based on inverse perspective transformation. Firstly, the optimal threshold method is applied to binarize the road image. The experiment proves that the optimal threshold method achieves a more stable effect than the Otsu algorithm under the conditions of road illumination and weather changes. Then, the top view with the angle of the horizontal plane is converted into a front view by using the inverse perspective transformation. Finally, the binarized image after inverse perspective transformation is fitted by K-means clustering algorithm. The final results show that the proposed approach is ideal for lane-line detection.

References 1. Fang MX (2017) Researches on intelligent traffic light based on machine vision. University of Electronic Science and Technology of China, Chendu 2. Zhang R, Wang H, Zhou X et al (2012) Lane detection algorithm at night based on distribution feature of boundary dots for vehicle active safety. Inf Technol J 11(5):642–646 3. Fang H, Jia R, Lu J (2010) Segmentation of full vision images based on color and texture features. J Beijing Inst Technol 30(8):935–939 4. Wang Y, Teoh EK, Shen D (2004) Lane detection and tracking using B-Snake. Image Vis Comput 22(4):269–280

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5. Gao F, Jiang D, Xu G et al (2012) A 3d curve lane detection and tracking system based on stereovision. CICTP 1247–1258 6. Gualain DO, Hughes C, Glavin M et al (2012) Automotive standards grade lane departure warning system. IET Intel Transp Syst 6(1):44–57 7. Zhang Z (2010) Digital image processing and machine vision. People’s Posts and Telecommunications Publishing House, Beijing 8. Ostu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(1):62–66 9. Liu XJ (2017) Research on lane detection and recognition algorithm under complex road image. Henan University of Technology, Zhengzhou 10. Hang YG, Yang JH (2009) Lane detection based on inverse perspective mapping and hough transform. J Yunnan Univ 31(1):104–108 11. Bertozzi M, Broggi A, Conte G (2000) Vision based automated vehicle guidance: the experience of the ARGO vehicle. Real Time Imaging 6(4):313–324 12. Zhou SB, Xu ZY, Tang XQ (2010) New method for determining optimal number of clusters in K –means clustering algorithm. Comput. Eng. Appl. 46(16):27–31 13. Tao Y, Yang F, Liu Y, Dai B (2018) Research and optimization of K-means clustering algorithm. Comput Technol Dev 6(28):91–93

A Preliminary Study on the Attractive Factors of Car Headlight Form Design Huan Lin, Shijian Luo, Chen Zhu, Hongzhuan Ding, Huiming Yi, Ze Bian and Fangtian Ying

Abstract In the era of perceptual consumption, car styling design is an important factor that affects the customer’s purchase decision, which leads to competition among different car enterprises. Car headlight that is the most important component in the car body needs to be investigated. In this study, Kansei engineering and its related mathematical method that are widely used to translate customer’s feelings or perceptions to design features or elements are applied to the car headlight form design research. Firstly, perceptual words of car headlights and representative headlight samples are selected. Secondly, perceptual image space is built based on the semantic differential method. Then, the prominent perceptual words are obtained based on the principle component analysis and all samples on prominent perceptual words are ranked. The result shows that the sample shape design with a metaphor of “angry face” has higher perceptual scores that will leave a deep impression on customers and have more attractiveness. The proposed design strategies can be taken as a design reference to car designers or car companies. Keywords Car headlight Form design


Kansei engineering
Principle component analysis


1 Introduction In the era of perceptual consumption, car styling design is an important factor that affects the customer’s purchase decision, which leads to competition among different car enterprises. Car headlight that mounted on either side of the head of a car

H. Lin (&)
S. Luo
Z. Bian
F. Ying College of Computer Science and Technology, Zhejiang University, Hangzhou 310013, Zhejiang, China e-mail: [email protected] C. Zhu
H. Ding
H. Yi College of Mechanical Engineering, Quzhou University, Quzhou 324000, Zhejiang, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_29

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is one of the key components in the car body. An eye-catching headlight design will contribute to the physical attractiveness of the car. Kansei engineering [1] is a theory that explores the relationship between the perceptual needs of people and the design characteristics of things. By means of Kansei engineering, fuzzy perceptual needs and images of consumers are able to be translated into product design elements and features. Kansei engineering theory is firstly developed in automobile industry [2] and then widely applied to many other fields such as electronics [3], fashion [4], food [5], interior [6], and so on. However, current headlight design mainly depends on the designer’s subjective experiences and preferences and there are rare studies on headlight form design from Kansei engineering perspective. This paper aims to investigate the customer’s perception of car headlight form design and give design suggestions to car designers and car companies.

2 Methodology 2.1

Kansei Engineering

Kansei engineering theory was proposed by M. Nagamachi forty years ago, and it is well known in the world as an ergonomic technology for producing a new product [7]. Kansei engineering has been developed as a productive research discipline, highly connected to the industrial world, innovations, and market successes [8]. Based on Kansei engineering framework, the general research steps used in this paper are as follows. (1) collection and selection of perceptual words; (2) collection and selection of product samples; (3) correlation of the perceptual words with product samples based on a mathematical model which is the principal component analysis; (4) analyzing the design features and characteristics of the product.

2.2

Prominent Perceptual Words Analysis

Based on the Likert scale rating, perceptual data from users are collected. Then after the average perceptual value is obtained, all data greater than zero are set as set A, and the average values of elements in the set are set as
a. All data less than zero are set as set B and the average value of elements in the set B are set as
b. The data set greater than
a is A′, and the data in A′ indicate that the sample tends to the right perceptual word on the Likert scale. The data set less than
b is B′, and the data in B′ indicate that the sample tends to the left perceptual word on the Likert scale [9]. Data in both two sets indicate that respondents have a stronger feeling of perceptual words corresponding to the sample.

A Preliminary Study on the Attractive Factors …

(

(

259

)
A ¼ xij jxij [ 0; i ¼ 1; . . .; m; j ¼ 1; . . .; ng
B ¼ xij jxij \0; i ¼ 1; . . .; m; j ¼ 1; . . .; ng

ð1Þ

)
A0 ¼ xij jxij [
a; i ¼ 1; . . .; m; j ¼ 1; . . .; ng
B0 ¼ xij jxij \
b; i ¼ 1; . . .; m; j ¼ 1; . . .; ng

ð2Þ

Based on Eqs. (1) and (2), the data within average values greater than
a and less than
b are extracted which represent prominent perceptual images. Principle component analysis is the mathematical method used in this study. Principal component analysis (PCA) is a multivariate statistical method to investigate the correlation between multiple variables. It aims at deriving a few principal components from the original variables, so that they retain as much information as possible about the original variables and are not correlated with each other [10]. The principal components of the samples are represented as Eq. (3). 8 F1 ¼ l11 zx1 þ l12 zx2 þ


þ l1n zxn > > < F2 ¼ l21 zx1 þ l22 zx2 þ


þ l2n zxn ... > > : Fm ¼ lm1 zx1 þ lm2 zx2 þ


þ lmn zxn

ð3Þ

where F1, F2, …, Fm are the principal component variables, zx1, zx2, …, zxn is the vector of data matrix after standardization (m < n), and lij is the loading of factor Fi for variable zxj. The principle component load indicates the degree of correlation between the principle component and original variables. Based on the frequency of occurrence of perceptual words and the high absolute value of principle component load, prominent perceptual words will be determined.

2.3

Research Process

This study takes car headlight form design as the research subject. Typical headlight samples and related descriptive words are selected. By the means of semantic differential and principle component analysis, prominent perceptual words are obtained which take as the basis of judgement on headlight form design. Then, final Kansei scores are calculated and customer’s perception on headlight is analyzed and discussed. The Kansei evaluation result indicates the car headlight design suggestions to car designers and manufacturers.

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3 Case Study 3.1

The Screening of Perceptual Words

By means of searching for car headlight information in automobile magazines, advertisements, network, and literature research, totally 121 descriptive words of the commentary on car headlights are acquired. Then the perceptual words were classified and those words which are not common words describing the car headlight were screened out by expert review. There are 69 words selected for further clustering. Pairing those words with opposite meanings and 45 pairs of adjectives were defined to be screening by expert panel. During the screening, 18 college students majoring in industrial design were invited to fill the questionnaire which requires them to select the top ten pairs of words that can best describe car headlight. The selected words were sorted according to the number of times they are selected. Through comparison of words category and meanings, finally, seven pairs of descriptive adjectives were screened out. Seven pairs of words are “ugly– beautiful,” “mediocre–distinctive,” “complex–simple,” “plain–gorgeous,” “dull– dynamic,” “introverted–wild,” and “unrecognizable–easily identifiable.”

3.2

The Screening of Typical Headlights

A large number of automobile pictures within front view were collected from various automobile websites. Through comparison and selection, 152 pictures were firstly defined for further expert evaluation. Then, eight product designers from car company were invited to be an expert panel and they screened 12 typical car front view pictures with a distinctive headlight out by clustering and analogy analysis based on the headlight form design. All of those samples are coming from nine popular brands in the market such as Jeep, BMW, Porsche, and so on. In order to highlight the headlight form and keep headlight form lifelike, pictures were dealt with Photoshop software and shape of the headlight is extracted as well, as shown in Table 1. Logo of the car was removed to reduce the brand influence on consumers.

3.3

Establishing Perceptual Image Space

A perceptual image investigation questionnaire was firstly designed in order to get a consumer’s perceptual data. In the survey, basic anthropometry data, semantic differential scale rating, and consumer’s preferences rating were included. What needs to be pointed out is that in the semantic differential (SD) method, 7-point Likert scale was used for rating.

A Preliminary Study on the Attractive Factors …

261

Table 1 Representative headlight design sample Sample 1

Sample 2

Sample 3

Sample 4

Sample 5

Sample 6

Sample 7

Sample 8

Sample 9

Sample 10

Sample 11

Sample 12

Secondly, a total of 60 people among the age from 20 to 45 who have at least one-year driving experience were recruited. There are 29 females and 31 males. Participant’s major was not limited in this research. All of the participants filled the survey based on their own perception of car taillight.

3.4

Statistical Analysis

3.4.1

Reliability Analysis

SPSS software was used to analyze the data. Before analyzing the perceptual data, the whole perceptual data reliability is tested at first [11]. Cronbach’s Alpha coefficient is a commonly used method to check the data reliability. When Cronbach’s Alpha coefficient value is above 0.8, it indicates that the scale has a very good internal consistency [12]. In the reliability analysis results of this study, Cronbach’s Alpha coefficient is shown as 0.942 which is above 0.8, which means the perceptual data is reliable.

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Prominent Perceptual Words Analysis

Firstly, averaging the data of seven pairs of perceptual words is based on the SD method. The number which is greater than zero means that the sample image tends to the word on the right of the scale. Secondly, prominent perceptual words in each sample are determined according to Eqs. (1) and (2). Then, by means of principal component analysis based on SPSS software, two principle components were obtained. Based on the total variance interpretation, we can find that the first two principal components can summarize 94.901% information of original data. There are two principle components extracted. The first component contains perceptual words such as “ugly–beautiful,” “mediocre–distinctive,” “plain–gorgeous,” “dull–dynamic,” “introverted–wild,” and “unrecognizable–easily identifiable,” and the second component contains “complex–simple.” We can find that two factors of headlight form impact on user perception are the aesthetics and design complexity. According to the principal component analysis result, the key words with high occurrence frequency and high principal component loading are selected, which is beautiful, distinctive, gorgeous, dynamic, and wild. Those selected words indicate customer’s prominent perceptual images on the car headlight. Then correlating the selected keywords with each sample, the scores on five prominent perceptual words are summed up (Table 2).

3.4.3

Design Interpretation

According to the data result, customer’s prominent perceptual words are: beautiful, distinctive, simple, gorgeous, dynamic, and wild, and the top two samples in the ranking are sample 12 and sample 6. The scores of the top two samples are much higher than sample 4 which ranked the third. By comparison with different samples and their scores, it is found that the

Table 2 Scores of samples on key words Sample 1 2 3 4 5 6 7–11 12

Keywords Beautiful

Distinctive

Gorgeous

Dynamic

Wild

Score

/ / / 0.652 0.609 1.087 / 0.986

/ / 0.681 0.783 0.739 1.043 / 1.246

/ 0.71 0.696 / / 0.783 / 1.058

/ / 0.609 0.768 / 1 / 1.145

/ 0.667 / 0.783 / 0.797 / 1.159

0 1.377 1.986 2.986 1.348 4.71 0 5.594

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Table 3 Headlight form design ranking and its design metaphor Headlight design ranking

Metaphor

Fig. 1 Metaphor of “angry face”

α

eyebrow

headlight shape with a metaphor of “angry face” tends to attract customer’s attention and have higher perception scores than other shapes with a metaphor of “dull face” (Table 3). Looking into the samples that the score is zero, the metaphor of most of the headlight shapes is a little ambiguous but some of them tend to be “angry face.” It indicates that the degree of “angry” which corresponds to the angle of inclination of “eyebrow” may have a big influence on the customer’s perception (Fig. 1).

4 Conclusion In this paper, the car headlight form is investigated based on the method of Kansei engineering. At first, customer’s perception of headlight form is quantified by the semantic differential method. Then, principle component analysis is used to analyze the customer’s perception data and two design factors that are esthetics and design complexity are extracted. Meanwhile, prominent perceptual words are obtained based on the mathematical model. Finally, the perceptual scores of headlight form among all investigated samples are ranked by summing up key perceptual words scores. The result shows that the headlight shape with a metaphor of “angry face”

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tends to have a stronger visual impact on customers that is likely to attract their attention than the metaphor of “dull face.” The inclination angle of “eyebrow” in the “angry face” will be further investigated in the next study. The proposed car headlight design insights can be taken as a design reference for car designers or car companies. Acknowledgements This research was supported by the National Natural Science Foundation of China (No. 51675476 and No. 51175458).

References 1. Nagamachi M (1995) Kansei engineering: a new ergonomic consumer-oriented technology for product development. Int J Ind Ergonom 15(1):3–11 2. Horiguchi A, Suetomi T (1995) A Kansei engineering approach to a driver/vehicle system. Int J Ind Ergonom 15(1):25–37 3. Kuang J, Jiang P (2009) Product platform design for a product family based on Kansei engineering. J Eng Design 20(6):589–607 4. Green A, Chattaraman V (2018) Creating an affective design typology for basketball shoes using Kansei engineering methods. In: International conference on applied human factors and ergonomics. Springer, Cham, pp 355–361 5. Ushada M, Okayama T, Suyantohadi A et al (2017) Kansei engineering-based artificial neural network model to evaluate worker performance in small-medium scale food production system. Int J Ind Syst Eng 27(1):28–47 6. Wang MF, Hsiao SW (2018) A Kansei-oriented method for interior design. In: 2018 IEEE 22nd international conference on computer supported cooperative work in design (CSCWD). IEEE, pp 485–490 7. Nagamachi M, Lokman AM (2016) Innovations of Kansei engineering. CRC Press, Boca Raton 8. Levy P (2013) Beyond Kansei engineering: the emancipation of Kansei design. Int J Design 7 (2) 9. Su C, Fu LM, Li S et al (2016) Design method in exterior color based Kansei engineering and principal component analysis. J Jil Univ Sci Technol 46(05):1414–1419 (In Chinese) 10. Jolliffe I (2011) Principal component analysis. International encyclopedia of statistical science. Springer, Berlin, Heidelberg, pp 1094–1096 11. Ding M (2011) Study on product color design model and method based on image. School of Mechanical Engineering, Dalian University of Technology, Dalian 12. Qiu HZ (2013) Quantitative research and statistical analysis—SPSS (PASW) data analysis example analysis. Chongqing University Press, Chongqing

Design and Optimization of Command Software Interface Chunfeng Zhu, Danhua Sun, Zuohui Bao and XiaoFei Zhai

Abstract Command software is the soul and core of the command system. With more and more functions and more and more complex use, the usability problem becomes more and more prominent, which becomes the bottleneck restricting the effectiveness of weapons and equipment. In reality, the development of command software is usually carried out by third-party technicians. However, the third-party technicians have always focused on software decision-making model and function realization, but there is little concern about software interface design. Based on my own operational experience, this paper puts forward my own understanding and cognition of the current commonly used command software interface design problems. Keywords Software interface


Design
Optimization

1 Introduction The software interface is the face of the software, the most direct layer of interaction with the user [1]. The man–machine interface of the command system is the medium and dialog interface between the operator and equipment [2–5]. Therefore, the effect of man–machine interaction directly affects the operation efficiency and function realization. As a professional command system operator, I have operated many versions of command software and found some unsatisfactory places in use. Here, I put forward my own understanding and cognition for the reference of relevant personnel.

C. Zhu (&)
D. Sun
Z. Bao
X. Zhai Zhengzhou Campus, CPLA, Army Artillery and Air Defense Forces Academy, Zhengzhou 450052, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_30

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2 Don’t Hide Commonly Used Information All the time, the development of command software is undertaken by third-party technicians, which is seriously disjointed from the military operators [6]. Although, the research and development units have collected a lot of opinions from users. They have made a lot of efforts in the design of software interface, but most of the work is used in the modification of the interface, which always gives people the feeling of operating a game on the first use. Our operating software is to command operations and improving combat effectiveness is the only standard. If we only pay attention to the gorgeous interface and lose a lot of intuitive and practical things, it will become a burden. For example, the user gives his opinion on the previous version that the software window is too small to display many things, so many folding menus are designed in the new version of the software. Just think, in the process of command, every second counts, and there is no time to find the menu singly. Even if you are very skilled and can find the menu directly, there will be a large number of mouse movements, as shown in Fig. 1. If all available menus are expanded, the mouse trajectory will become simpler, as shown in Fig. 2. It can be seen that the expansive menu can reduce the mouse trajectory by up to two times in general. On average, 2.057 s can be saved in time statistics, which is crucial in a battlefield where every second counts.

common

shoot

command command command one two three

command command five

shoot nine command command thirteen fourteen

Fig. 1 Mouse trajectory in folding menu

seven

command eight

command command eleven twelve

fourteen

command sixteen

Design and Optimization of Command Software Interface

command one

command two

command three

command nine

command ten

command eleven

command twelve

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command five

command six

command seven

command eight

command irteen

command fourteen

command fifteen

command sixteen

Fig. 2 Mouse trajectory in expanded menu

3 Highlighting of Important Information In air defense operations, there are often a lot of air information. How to display such much target information is appropriate? The original quotation of “Software is also combat effectiveness” [7] is as follows: If you ask, how to display the information of the current dozens of incoming targets? Many programmers will choose “tables” by coincidence. Each row has a target, and each column is the target number, longitude, latitude, azimuth, distance, altitude, speed, course, attributes of the enemy and ourselves, type and so on. The data can be accurate to minutes or meters, how nice!

It seems that this table displays the target information in a very good way, and it feels good in normal operations, but the situation will become completely different in actual combat conditions. In the process of organizing training, in order to study the accuracy of target information, we need to compare the data of two sites in the command system. My task at that time was to read out two specific batches of target information on one site for the comparison with the one at the other site. This is such a simple job, but it is extremely troublesome to operate because the number is small and the number of rows sometimes will also change (the automatic sorting function mentioned earlier). So, it is very difficult to monitor two or three batches of targets, which requires a high degree of concentration. This is just an experiment. Just imagine, if in the real battle, the commander will not have the energy to make a strategic decision. For this aspect, the interface design of human–computer on U.S. Army “Aegis” system is worth learning. It is not displayed in tables, but in intuitive blocks, as shown in Fig. 3. From top to bottom: Target batch number: 7037, yellow background means “threat!” Target model: Super Jaguar; Target type: Helo means helicopter; Target orientation and distance: 160 degrees, 25 miles; Target course and height: Arrowhead indicates being away, flying flat, 3000 m; Electronic warfare features; Whether the IFF identification of enemies and foes has been carried out;

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Fig. 3 Block display

Alerts button, it will light up when there is a new prompt for the target, and it will pop up the window to show the latest prompt when pressed. Among them, the small arrow in the sixth line, with eight directions to indicate the state of the target relative to itself, can be very intuitive to judge whether the target is near or far from itself, whether it is climbing or diving. However, the information shown in the table can only be judged and read by numerical changes. These small boxes only show the main information and can also show detailed information for the focused target. Such a display may not look good, but it is absolutely intuitive and convenient in the course of combat, which can display the most important information to the commander in the first time.

4 Simple and Clear Display Is the Best We have been keen on 3D display of battlefield situation for some time, and some products have been developed. The U.S. Army has also done a lot of work, but through a lot of theoretical analysis and prototype testing, it finally abandoned the 3D display, and adopted the combination of “top view on left–right side view on the right.” Because 3D is only visually good, but it cannot show more information than 2D, and the operation is more cumbersome, which requires dragging around with the mouse. At the same time, 3D can also lead to illusion and confusion, which cannot distinguish the real location of the target.

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5 Left–Right Layout of Double-Screen Information In order to display more information, the command system mostly uses up and down double-screen mode to display. But from the point of operation habits, the left and right layout is more convenient than the up and down layout. The design of up and down double screen may be mainly limited by space. However, if the space is properly designed, it can generally meet the left and right layout of the dual-screen display, and at least the main command seat can be changed to the left and right layout, so as to improve the convenience of operation.

6 Left–Right Design by Technical Means At present, the interface design of command software is mainly based on the experience and style of programmers, without too many experiments and tests, and without professional testing in a specific environment, so problems and shortcomings cannot be found. In this regard, we can learn from the two approaches of the U.S. Army. One is to optimize the layout by the eye tracker. That is to say, the test object is equipped with an eyeball focus tracker, and then the tester operates the software. In the process, the focus of the tester’s sight will be recorded and analyzed. And the sight focus staying most is kept in the middle, and the infrequently staying is put at the edge. At the same time, the movement order of the different interface elements is analyzed, so that the sequence of the interfacial elements is arranged in a certain order to avoid a large jump of sight on the screen. The second is to optimize the scheme through large sample comparative test. Avoid working behind closed doors, relying on experience and experimental objects, for different design schemes, we can organize multiple test teams to carry out large data statistics through actual operation, so as to optimize the best scheme.

7 A Design Legend The interface shown in Fig. 4 has been applied in a system developed by us, and the effect is quite ideal (This paper shows only the right interface design.). It can be used for reference by command software developers. The following principles are mainly embodied in Fig. 4. 1. The left screen is the target situation map, which is displayed in the largest area. 2. The upper-left folding part sets the window for the parameters of the situation map, and we can hide it after use without affecting the view. 3. The right screen is the operation area, where the main operations are concentrated.

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Fig. 4 Design legend

4. The upper-left corner of the right screen displays the main information of the target in a checkered style. The background of the square is divided into three colors according to the degree of threat and is consistent with the color of the air track on the left side. When it is necessary to pay attention to a group of targets, double-click the target square and the detailed parameters will be displayed on the right side. 5. The command area is below the screen. Common commands are placed below the right screen, and infrequent commands are placed below the left screen. The data can meet the command requirements as far as possible, and the data which cannot be included will be input through the command text input area. 6. Set the unit selection area. First, select the accept unit of command unit, and then click to issue the order.

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7. In order to facilitate commanders to grasp the situation, it sets the receiving and reporting area of unit commands, and six units can be selected to display the recently received commands and reported commands. 8. Two other view display modes are set in the middle, which can be selected according to customer requirements.

8 Conclusions The U.S. Army has proposed “4 s decision-making advantage” in the optimization of command software design. That is to say, without changing the hardware equipment of the weapon system, the cognitive and decision-making time of human can be shortened by optimizing the command software interface, so commanders can gain 4 s decision-making time. It can be seen that the interface design of command software is so important that it is no wonder that the U.S. Army will use more than ten years to continuously optimize and improve. In this respect, we must re-recognize, change the traditional understanding, put the experimental environment into a specific environment, constantly improve and perfect the interface design of command software and develop a better command system.

References 1. Lu Yinan Z, Hongxia W (2012) From the point of view of software testing, this paper discusses software interface design. Autom Command Comput 2012(4), 24 2. Zhou S (2007) Human-machine interface design. Science Press, Beijing 3. Li L (2004) Human-machine interface design. Science Press, Beijing, p 1417 4. Zhang G (2006) User interface design (trans: Jianli L). Electronic Industry Press, Beijing 5. Luo S (2002) Human-machine interface design. Machinery Industry Press, Beijing 6. Chen J, Jin C, Wei K (2013) Study on usability problem of command and control software for armored vehicle. Comput Meas Control 21(8):2278–2281 7. Mohong U.S. Navy Learning Station (the public) Software is also combat effectiveness: enjoy carefully the U. S. Army “Aegis” system human-computer interface. [EB/OL]. http://docin. com/touch/detail.do?id=2025863114

A Subjective Assessment Method of Aerospace Image Quality Based on Human Visual System Wuyuan Zhou, Haoting Liu, Chang Guo, Weidong Dong, Shuo Yang, Shunliang Pan and Guoliang Tian

Abstract Aiming at the problems of blur, noise and contrast distortion in aerospace images, a subjective image quality assessment method based on human visual characteristics is proposed in this paper. First, the aerospace image database with different blur, noise and contrast distortions is simulated by 3D modelling software. Second, the subjects are required to give three image quality scores based on the indexes above, respectively. Third, the correlations of three indexes’ scores are calculated by the Pearson formula and then different weights are given to the indexes based on the calculated correlation coefficient above. Finally, the modified subjective image assessment scores can be obtained by the multi-factor model. The proposed subjective evaluation model takes into account the influence of multiple factors that can show the characteristics of images comprehensively. Many experiment results have verified the correctness of the proposed method. Keywords Aerospace image quality assessment Multi-factor model





Human visual characteristics
Subject

1 Introduction A space camera mounted on a spacecraft can quickly capture spatial information by means of an image, and the image quality directly affects the accuracy and reliability of the acquired information. However, due to factors such as the space environment and the imaging system, the quality of the acquired image data decreases in varying degrees, which greatly affects the subsequent processing and application [1, 2]. Therefore, through the quality analysis and evaluation of the W. Zhou (&)
H. Liu
C. Guo Beijing Engineering Research Center of Industrial Spectrum Imaging, University of Science and Technology Beijing, 100083 Beijing, China e-mail: [email protected] W. Dong
S. Yang
S. Pan
G. Tian Institute of Manned Space System Engineering, 100094 Beijing, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_31

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aerospace on-orbit image, the imaging control of the on-orbit camera can be guided and the application prospect of the image can be preliminarily estimated. Generally, there are two methods of aerospace image quality assessment: the subjective image quality assessment and the objective image quality assessment [3]. The subjective assessment method relies on the professional to score the image manually, which has a judgement of the overall clarity. However, the effect of multi-factor interaction on image quality is not considered, and the detailed features of the image are ignored. The objective image quality assessment evaluates the image quality according to the image algorithm, including three methods: reference, semi-reference and no reference. But its most obvious defect is that it evaluates the image without considering human’s subjective feelings [4–6]. Therefore, it is significant to propose a new method that combines the advantages of both. In consideration of the effect of multi-factors, a subjective image quality assessment method based on human visual characteristics is designed. Firstly, the aerospace image simulation database is established through 3D modelling software. Then, the subjects are organized to subjectively score the images based on different indexes. Finally, the parameters of the multi-factor model can be obtained by analysing the score data; the principal-factor-based image scores can be computed according to the multi-factor model.

2 Selection of Image Quality Indexes for Aerospace Application The acquisition environment of aerospace image is complicated. Generally speaking, there are several problems. First, the sources of light are varied, which contain sunlight, starlight and the reflected light from the spacecraft. Obviously, the light spectrum also varies widely. These will change the contrast of image. Second, the lack of image exposure time and the processing of analog-to-digital conversion during image transmission may generate imaging noise. Third, the vibration of camera inevitably exists during the flight task which may blur the image too. Moreover, the relative speed of movement between the satellite sensors and the observation target is definitely fast which will lead to a low-speed focal length adjustment. Due to the above phenomena, the quality of aerospace images may decrease to different extents. Therefore, the corresponding blur, noise and contrast are proposed as three indexes for evaluating aerospace images. When simulating images, blur can be obtained from the original image through the Gauss filter, and the bandwidth of the filter determines the blur degree of the distorted image. Noises can be added by generating Gauss noise with different variances. And the contrast change in image causes less structural distortion; thus, it can be obtained by changing the value between different pixels.

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3 Proposed Subjective Image Assessment Method 3.1

Subjective Image Assessment Using Multi-factor Model

When observing an aerospace image, the image stimulation to human eyes is a combination of different signal amplitudes and frequencies. The response of the human eye to a stimulation is related not only to the original signal itself, but also to other exterior information. Therefore, when the multiple incentives coexist, one incentive interferes with the other and makes the visual threshold change. This phenomenon which is also called as the contrast mask characteristic is in line with the general visual habits of observation and cognition. Due to the existence of contrast mask characteristics, some distortions in aerospace images may be ignored by human eyes, while others will be enhanced, resulting in an inaccuracy of subjective image quality assessment. To conquer this problem, three indexes are utilized in aerospace image quality assessment in this paper. A multi-factor-based subjective image quality assessment method is proposed here [7]. First, the subjects assess the image according to a single factor, such as blur, noise or contrast, respectively, and then record their scores. Second, when calculating the main factor level of image quality, the interference of other two factors is also considered. Finally, a linear weighted method is employed to obtain the assessment score. The formula which is called as the multi-factor model is shown in (1). Main factor level ¼ blur score  a þ noise score  b þ contrast score  c

ð1Þ

where a, b, c represent their respective weights.

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Assessment Data Processing Method

The assessment data processing aims to set the weight parameters in multi-factor model after processing the obtained original subjective assessment score. Without loss of generality, let us define a symbol Zkmn as an evaluation score, where k is the number of kth subjects; m means the mth image; and n represents the nth evaluation index. For an image, the final score is to calculate the averaging score of all the individual scores. The calculation method is shown in (2). We use the Pearson linear correlation coefficient to analyse the correlation between any two indexes of three individual scores [8]. The calculation method is given in (3). The closer the correlation coefficient is to 1 or −1, the stronger the correlation is. And the closer the correlation coefficient is to 0, the weaker the correlation should be.

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Zmn ¼

5 1X Zkmn 5 k¼1

P P P M xi yi  xi yi r ¼ qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P P P ffiqffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P ffi M x2i  ð xi Þ2 M y2i  ð yi Þ2

ð2Þ

ð3Þ

where m = 1, 2, …, k represents the subject and n means a certain evaluation index, such as blur, noise and contrast. Symbol r means the Pearson coefficient, M means the number of images, and xi and yi represent the score of different indexes.

4 Experiments and Discussion A series of experiments are performed in this paper to test the correctness of the proposed method. The C and MATLAB are utilized to develop a software in Windows 10 Home Edition operating system. The hardware environment of this experiment is Intel Core i5 4200U processor, 4 GB RAM.

4.1

Image Acquisition

The original image in the experiment is produced by simulating the aerospace image through 3D modelling software. The evaluation indexes of aerospace image quality based on human visual system include blur, noise and contrast. When simulating these image data, the original image is processed by Gauss blur, adding Gauss noise and changing image contrast. The parameters of each index are set to seven levels, so a total of 7 * 7 * 7 = 343 images are simulated. The simulated images can meet the requirements of real aerospace image quality evaluation. Some simulation pictures are shown in Fig. 1.

Fig. 1 Simulation images of different blur, noise and contrast factors

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Condition Setting of Subjective Assessment Experiment

After the colour vision test, five students with normal vision and some knowledge of image processing were organized to carry out this experiment. According to the ITU-R BT.500-13 image quality test standard, the image is subjectively scored. A 14-in. high-definition LED display with a resolution of 1366 * 768 and peak brightness of 50 cd/m2 was used in the experiment. In order to avoid the influence of ambient light in the experiment, the experimental illumination condition is of white light with low brightness. It is necessary to train all the subjects and explain the purpose, content and indexes of experiment in order that they give reasonable evaluation scores according to the indexes. Before the evaluation experiment, each subject had 5 min to adapt to the environment. The distance between their eyes and the monitor was 50 cm. Subjective scoring is based on a ten-point system, in which 1 represents the worst quality and 10 represents the best quality. When displaying the experiment data, the original ten-point image is given, and all images are disrupted in order to avoid the appearance of a certain index changing in the light of the same rule, which affects the reliability of subjective experiment. In the experiment, each image was projected for 20 s, during which the subject scored image according to the evaluation indexes.

4.3

Experiment Results

After the evaluation experiment, lots of data can be accumulated. To process these data, their average score is regarded as the final score for the index. The original subjective evaluation scores of 343 images are drawn together in the scatter plot in Fig. 2. It is clear from Fig. 2c that there is a significant correlation between blur score and contrast score, while it is obvious that the correlation between the other two groups of indexes does not exist from Fig. 2a, b.

Fig. 2 Scatter plot of the scores of all images for different indexes

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Table 1 Pearson linear correlation coefficient among three evaluation indexes Blur score Noise score Contrast score

Blur score

Noise score

Contrast score

1 0.101 0.634

0.101 1 0.086

0.634 0.086 1

Table 2 Weight parameters of the proposed method

Blur level Noise level Contrast level

a

b

c

0.7 0.15 0.25

0.05 0.7 0.05

0.25 0.15 0.7

In order to quantitatively show the correlation between different indexes, the Pearson correlation coefficient is calculated and the results are shown in Table 1. The Pearson coefficient between blur and contrast is 0.634, which means there is a significant correlation between them. The Pearson coefficient between blur and noise is 0.101, and the result between noise and contrast is 0.086, which means they have little relevance. In multi-factor model, normally the sum of weight parameters a, b and c is 1 and the weight of the main factor is relatively high, so it is set to 0.7 in this experiment. Considering that there is a significant correlation between blur score and contrast score, the weight parameter of them is set to 0.25 and the other parameter is set to 0.05. When calculating the noise level of the image, there is no significant correlation between noise and blur, and noise and contrast, so the parameters of them can be set to 0.15. The weight parameters of the multi-factor model are shown in Table 2. After the above parameters are obtained, the modified subjective image quality assessment scores can be calculated using the multi-factor model. Twenty subject scores of one image based on different assessment method are shown in the line chart in Fig. 3a–c. Figure 3d is the score standard deviation histogram. It can be seen from the graph that the evaluation method by using multi-factors on line chart fluctuate less and the standard deviation by using multi-factors is smaller. Therefore, the proposed method has good stability and reduces the individual error.

4.4

Discussion

In the past, the subjective evaluation method only gave one score considering the overall characteristics of image, and the detailed description of image was not specific enough. The proposed method fully considers the human visual

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Fig. 3 Line chart of twenty subject scores and histogram of scores’ standard deviation

characteristics in the assessment and gives different weights for different factors, which can fully display the image detail features. Furthermore, the proposed method is very stable and generalized, and is less affected by the individual subject. No matter which single-factor assessment method is used, its standard deviation is higher than the multi-factor model method, so the multi-factor assessment method is more reliable. The subjective image quality assessment method based on multi-factor model proposed in the paper has a good application in the subjective quality assessment of aerospace images; however, it also has some disadvantages. For example, due to the limit of the amount of image data, the accuracy of multi-factor model needs to be improved.

5 Conclusion In this paper, a method of subjective image quality assessment applied in aerospace image is presented. This method combines the visual characteristics of human eyes and takes into account the influence of multi-factors on image quality. A multi-factor model for calculating subjective image quality score is proposed. Comparing with other methods, the proposed method can be applied to subjective image quality assessment for aerospace image well and has good stability.

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Acknowledgements This work is supported by the National Natural Science Foundation of China under Grant No. 61501016 and the open project of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect under Grant No. SKLIPR1713. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of University of Science and Technology Beijing. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Liu YC, Liu L (2001) Orbit determination using satellite-to-satellite tracking data. Chinese J Astron Ast 1(3):281–286 2. Sharma J (2000) Space-based visible space surveillance performance. J Guid Control Dynam 23(1):153–158 3. Chandler DM (2013) Seven challenges in image quality assessment: past, present, and future research. ISRN S P 2013, pp 1–53 4. Winkler S (2012) Analysis of public image and video databases for quality assessment. IEEE J-STSP 6(6):616–625 5. Fang YM, Zeng K, Wang Z et al (2014) Objective quality assessment for image retargeting based on structural similarity. IEEE J EM SEL TOP C 4(1):95–105 6. Hou C, Ma T, Yue G et al (2017) Multiply-distorted image quality assessment based on high-order phase. LOP 54(7):071001 7. Sheikh HR, Sabir MF, Bovik AC (2006) A statistical evaluation of recent full reference image quality assessment algorithms. IEEE T Image Process 15(11):3440–3451 8. Verdult V, Verhaegen M (2005) Kernel methods for subspace identification of multivariable LPV and bilinear systems. Automatica 41:1557–1565

The Cabin Layout Project of the Ergonomic Evaluation Methods Study Sijuan Zheng, Li Li, Wenjun Guo, Fang Xie, Liang Ling and Zhongliang Wei

Abstract In the cabin design, the cabin layout is claimed tight and optimizes work environment. The cabin is a narrow space, and there are many equipment in the cabin. It will produce impact influence for the operation comfort and security. Therefore, the cabin design should sufficiently use space, and it is a security and useful environment for people. It is an important ensure, during which it is a long time and efficient [1]. The cabin design has many traits, such as the subsystem and discipline’s coverage wide, many design targets, complicated limit condition. Between design, task target’s independence is poor. They exist on mutual contradiction and restriction, and it will take repeated design. Therefore, the cabin layout valuation is a very necessity. Keywords Cabin layout


Evaluation
Ergonomic evaluation

1 The Establish of the Ergonomic Evaluation System The ergonomic evaluation is one of the system engineering. According to the characteristics of the system described, construct a whole level that can objectively reflect system from several angles of views and the layers. A whole level includes the system element’s allocation and the system structure’s arrangement. Every element is an index factor that it describes the evaluated object’s characteristic. The correlation is the layer structure of the system between indexes [1]. We analyze the characteristic of the cabin ergonomic evaluation that we compare the different methods of the ergonomic evaluation. We are certain the key technique of the cabin ergonomic evaluation, and establish the comprehensive valuation index sign system. We standardize processing and synthesize an index value to the valuation index. S. Zheng (&)
L. Li
W. Guo
F. Xie
L. Ling
Z. Wei China North Vehicle Research Institute, Huaishuling No. 4 Court, Fengtai District, Beijing 100072, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_33

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The Establish Principle of the Evaluate Index System

The ergonomic has conceptual ambiguity, measure standard’s diversity and evaluation model’s complexity that they decide the index system’s complexity. Concrete body layer and amount of the index sign are more now, scope compare breadth, make sure that same layer is each to evaluate index of the important sequence be more difficult, processing and set up the process more complicated etc. Thus, it easily cause falsity system hypostatic characteristic [2]. Therefore, set up the index system has to follow a certain basic principle: a. Science principle. Evaluation of the index system wants to be very objective to really reflect cabin ergonomic of the proper quality and actual circumstance; there is science basis, do not vary from person to person. b. Objectivity principle. The index system has to ask for help of science method to reason logical analysis to predict, cannot randomly guess. c. Complete principle. Index system overall and comprehensive reflect cabin ergonomic whole characteristic of effect. d. Sensitivity principle. When the system main characteristic change, system index can the intelligently change. e. Compare principle. The index system has to promise to differently evaluate object contrasting in the equal and compare worth system, cannot include some indexes which have obviously “tendency”; meanwhile, the index system should also have general and compare characteristic. f. Operability. Evaluate index has to have explicit meaning and request simple, explicit and practical. And it should have measurability and quantifiable characteristics; meanwhile, some index hard to measure and hard to collect that should try to look for the replaceable index, look for the path of investigating the collection index data, to confirm statistical methods of the data estimate, and thus an index system real realized value. The request of different evaluation method to index system may exist on some differences, and the index system should be consistent with cabin ergonomic design’s principle. What needs to be explained is that this principle is the general principle which guides the index system of the structure evaluation and wants practical confidence in physically applied, but also need a vivid usage.

1.2

The Process of the Evaluate Index System Establish

Cabin ergonomic index system structure be the thinking process of the dialectical logic of a “concrete–abstract–concrete”, is known to cabin ergonomic design of gradually and deeply turn, gradually fine, gradually perfect, gradually systematize process, is divided into the theories preparation, index system’s selection, index

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Fig. 1 Comprehensive evaluation index system establish flow chart [5]

system’s examination, index system’s application, etc. These four links can also be a cabin ergonomic design of the whole design process (Fig. 1).

1.3

The Index Selects Method

The system evaluation index’s select mostly carries on some concrete target and rarely involves evaluation index selection’s method theories of research. Therefore, this research is carried on some beneficial investigates to the cabin ergonomic and tries to use a comprehensive method, analytical method, compound method and the index attribute cent set method, etc. a. The comprehensive method The comprehensive method is means to have already exist of concrete system evaluation index certain of standard carry on comprehensive, make its systematic, that is a kind of index system structure method. To ergonomic evaluation index system which there has been do to categorize a sorting further, thus initial construct an opposite overall and have certain the cabin of the reasonableness ergonomic

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evaluation index system. So, the beginning which the comprehensive method especially is applicable to indexes set up and for existing evaluation index system of perfect and development. b. The analytical method The analytical method means to press the logic classification cabin ergonomic target of the evaluation to divide the line into some dissimilarities to constitute part of or different on the sides(namely subdivision mark) downward, each mark gradually subdivides, formation of all the levels cent target or standard, until each part can use concrete of metered or settle sex index to describe with realization. Therefore, the analytical method is to construct an index system the most in common use with the most basic method. What needs to be pointed out is that the end become of the layer structure of the index system should be a tree form structure, for minority individual net of the layer structure, need to pass enlargement and adjust the tree form that some subdivision object methods make to turn. Another, from the analytical method structure comes out of index system, its constitute index generally can more satisfy independence request. c. The compound method The compound method means an index constructs method that according to evaluation of effective demand and mathematics rule, a few independence of single valuate index combined together, the formation of new compound index. The compound method passes the form that the index comes together and makes melodrama object, respectively, the advantage strengthens and overcomes original parts of weakness. Moreover, some indexes have compound connotation can depict several problems. For example, “the personnel’s experience” can reflect the operation personnel’s completion circumstance of the respect work degree, mission and operate the ability to reach several aspects of mark circumstances, etc. the characteristic index of the level in the meantime to some extent. d. The index attribute cent set method The index attribute cent set method means to conceive outline, a kind of index structure method that the index constitutes from the index different attribute angle and the manifestation. Because the evaluate index has many different attributes, there is different manifestation can try to conceive outline constitute of evaluate index from “absolute,” “opposite,” “average”, etc. What needs to be explained is that the four kinds of above thought methods which construct index can combine a usage in the cabin ergonomic evaluate index selection process.

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2 The Establishment and Optimizing Evaluate System In the cabin ergonomic’s evaluate research, it needs to be a reasonable of ergonomic valuate index system. As state above, the ergonomic design has to resolve two key problems, namely, the person control machine and person to accept information. The former mainly means the controller wants to be suited for the person’s operation and should consider that the person carries on the allocation of space and controller which operates; the latter mainly means that how the allocation of display mutually matches with controller and makes while operating the person observe convenience, quickly accurate. So the display and controller are the alternate and important medium of the man–machine interface middleman machines, and establishment index should emphasize consideration [3]. The research adopts the method that the expert consults with to carry on sieving sorting to the index complete works build up and passes to adjust the parts of indexes thus build up a set of integrity of passenger cabin layout design project of valuation system. After carry on comb analysis discover to exist some problems to the evaluation index system of initial establishment: (1) The first-floor index’s existence cross: The repeated contents appeared in the all levels index and suggest appropriate adjust to the index structure appear by avoid index to cross. (2) The index layer class connection is weaker: In consideration of show equip bright degree and frequency’s influence to cabin space, suggestion delete. (3) Index system structure optimizing: To the all levels, index carries on dismantling a cent to integrate with optimizing.

3 Comprehensive Evaluation of the Layout Scheme According to the evaluation index system’s establishment, applied misty layer analytical method quantified the weight of upper-level index, applies a subjective method of score quantified the attribute value of the underlying index, thus gets comprehensive evaluation result for the different cabin layout scheme. According to misty layer analysis calculate method, the first system index is quantified: I1 the cabin decoration, I2 the show quip suitability, I3 the operation equip suitability, I4 the cabin environment condition, I5 the whole vehicle adaptability, the misty layer that the establishment corresponds with each other repairs matrix. Through consistency examination compute, the power heavy value of one-class index is: fI1 ; I2 ; I3 ; I4 ; I5 g ¼ f0:256; 0:216; 0:216; 0:136; 0:176g:

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Secondly, to one-class index I1 the sub-index sign (for the second-class index) of the cabin total decoration is quantified: I1.1 the cabin space, I1.2 the current space, I1.3 exit and entrances and hatch, I1.4 the passenger chair, I 1.5 display layout, I 1.6 operation layout, I 1.7 functions layout, the misty layer that the establishment corresponds with each other repairs matrix. Through consistency examination compute, the power heavy value of the second-class index is: fI1:1 ;I1:2 ;I1:3 ;I1:4 ;I1:5 ;I1:6 ;I1:7 g ¼ f0:151;0:180;0:122;0:209;0:122;0:122;0:093g: In a similar way, as to the four index sign (I2 the show quip suitability, I3 the operation equip suitability, I4 the cabin environment condition, I5 the whole vehicle adaptability) are quantified. The misty layer that the establishment corresponds with each other repairs matrix. Through consistency examination compute, the power heavy value of the second-class index is: fI2:1 ; I2:2 g ¼ f0:5; 0:5g fI3:1 ; I3:2 g ¼ f0:5; 0:5g fI4:1 ; I4:2 ; I4:3 ; I4:4 g ¼ f0:25; 0:25; 0:25; 0:25g fI5:1 ; I5:2 ; I5:3 ; I5:4 ; I5:5 g ¼ f0:225; 0:225; 0:225; 0:225; 0:10g The end, the third-class index is quantified, because of the index system structure complications, first-floor index the amount be more. Combine a different layout project, pass the method that the expert score adheres to make a mark degree to carry on 10 cents to the evaluation of all first-floor indexes. 1–2 cent mean that the layout project varies the disregard think and completely not agrees with to match a design request; 3–4 cents mean that the comparison disregard of the layout project thinks and requests with design to exist bigger deviation; 5–6 cents mean that the layout project is general, basically meets a design request; 7–8 cents mean that the layout project is more ideal and requests with design to exist smaller deviation; 9–10 cents mean that the layout project is very ideal and completely meets a design request. According to the first floor of the index system score value and upper-level index of the power heavy coefficient, the method which passes to add a power calculation computes a dissimilarity layout project, respectively, of comprehensive evaluation result, layout project one of comprehensive grade point is 73.8, layout project two of comprehensive grade point is 76.4, layout project three of comprehensive grade point is 61.2, layout project four of comprehensive grade point is 69.7, layout project five of comprehensive grade point is 65.5. Project two is comprehensive to evaluate the superior project. What needs to be noticed is project two mediums the seat of pilot move behind the layout design will result in the homework of the personnel can see sex for showing interface of shortage and considers in response to the point in concretely the layout of the model number in the design [4].

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4 Conclusion This thesis according to ergonomic theory follows a certain principle, comprehensive selection index, establishes the evaluate index system, carries on the expert measures to review and integrates index, optimizing system adopts a misty layer comprehensive valuation method, to different cabin layout project carry on an evaluation, synthesizes score, optimizing the cabin layout project and will apply to a certain vehicle as a result up.

References 1. Weitie L (1997) Man-machine Engineering 2. ISO/IEC JTC (1999) Collaborative virtual environments contributions to MPEG-4 SNHC[S]. 1/SC 29/WG 11 N2802-1999 3. Gilson RD (1995) Situation awareness-special issue preface. Hum Factors 37(1):3–4 4. Adams MJ, Tenney YJ, Pew RW (1995) Situation awareness and the cognitive management of complex systems. Hum Factors 37(1):85–104 5. Wang Q (2016) The testing research on basic cognitive ability’s influence factors in special vehicle crewman. In: Man-machine-environment system engineering proceedings of the 16th international conference on MMSES

Development of an Aviation Emergency Coping Ability Evaluation Instrument Qingfeng Liu, Yang Lv, Xiaochao Guo, Fei Peng, Yu Bai, Jian Du, Zhengtao Cao, Duanqin Xiong, Bo Gu and Yanyan Wang

Abstract Objective: To develop an evaluation system on the emergency coping ability that is very important for effective performance in many emergency or extremely tasks, especially in aviation. Methods: An evaluation system and related hardware on emergency coping ability based on continuous tracking task and psychophysiology measurement were developed. The reversed operation was used to provide emergency situation. A total of 13 pilots completed the continuous tracking task. Performance which was measured by the average distance deviated from the target track and heart rate, heart rate variability indexes were recorded by the system and were analyzed for the validity. Results: Tracking performance of norm tracking task are significantly higher than those of different reversed tracking phases, especially that of the first six seconds. The participants adapted to the reversed operation gradually after 6 s. Mean heartbeat rate and LF/HF ratio also increased in reversed tracking phase. Conclusions: Index of emergency coping ability could be derived from the difference between tracking performance and psychophysiology change of norm tracking task and reversed tracking phase. The emergency situation model and evaluation system were developed and validated. Keywords Emergency coping ability Performance pilot


Mental attribute
Heart rate variability


Q. Liu
X. Guo
F. Peng
Y. Bai
J. Du
Z. Cao
D. Xiong
Y. Wang (&) Air Force Medical Center, Fourth Military Medical University, 100142 Beijing, China e-mail: [email protected] Y. Lv Aviation University of Air Force, 130022 Changchun, China B. Gu Air Force Flight Test Bureau, 710089 Xi’an, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_34

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1 Introduction Mental attributes such as responsive, coordination, divided attention, thinking ability, and emotion stability were considered important to pilots since the invention of aircraft [1]. These attributes measured in the selection system were relevant to the qualification rate of pilot training [2, 3] and air accident. Psychological selection was used to minimize flying training attrition. Continuous advances in information technology and aviation systems, especially growing computer ability and electronics promise to improve mobility, survivability, and sustainability of today’s aircraft systems. Therefore, successfully flying an advanced cockpit aircraft may depend more on mental attributes. Emergency coping ability, which ensures the effective performance in unusual and demanding condition, become essential for pilots facing high stressful environment, high workload, and high dangerous, especially in military aviation[4]. Evaluation of emergency coping ability of an applicant should reduce flying training attrition and increase the qualification of pilots. We developed a method to measure emergency coping ability based on continuous tracking task and reversed control tracking task combined with psychophysiology analysis.

2 Subjects and Methods 2.1

Subjects

A total of 13 male pilots with age of 35.2 ± 5.3 years and experience of 1742 ± 86 h total flight hours participated in the experiment. The ethics committee of the Institute of Aviation Medicine approved the experiment application and the participants signed an informed consent before the test. All pilots were on active service and have medical certification for flight. They guarantee the well sleep last night and no medicine taking within 24 h.

2.2

Development of Evaluation Instrument

Microsoft Visual Studio software was used to write the program of aviation emergency coping ability evaluation system. Continuous tracking task and reverse control tracking task were used to imitate flying operation and emergency environment. Tracking performance recorded by the program and heart rate variability recorded by portable physiological parameter instrument were analyzed to measure.

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a. Task design The program was developed for aviation selection. The task should be similar to aviation basic operation and have an emergency coping operation. It should have no complex operation and be easy to learn. Continuous tracking task was widely used in many pilots’ selection and psychological measurement programs, such as TBAS of USAF. Reversed task [5] was set suddenly in the test to induce emergency situation. b. Evaluation indexes Emergency coping ability could be reflected by operation performance and psychophysiology response. Therefore, heart rate variability (HRV) and the tracking deviation were combined to provide evaluation indexes. Tracking deviation from the target trajectory was an acceptable index to measure tracking performance. Comparison of tracking deviation of the normal task and that of the reversed task were done to measure emergency performance. HRV was related to the function of autonomic nervous system and emotion stability which was essential for well emergency coping. c. Writing program Microsoft Visual Studio was used to write program which composed 5 modules, including management module, task interface module, psychophysiology response record sensor, data analysis module, database of results data. The program structure was illustrated by Fig. 1. Program interface was illustrated in Fig. 2. The program runs on Widows xp or high-version operating system. Saitak control stick was used to control the blue circle to track the continuous moving green ball. The program recorded the distance

Fig. 1 Program structure illustration

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Fig. 2 Program interface

between the center point of the circle and the ball every 50 ms. Heartbeat signals were recorded concurrently from which HRV were calculated. d. Measurement method The participants were asked to control the blue circle with the stick to track the continuous moving green ball. The minimal deviation between the center point of the circle and the ball means the maximum tracking performance. The total test duration was 6 min. The former 3 min was normal tracking operation, and then reversed operation was suddenly set. The participant who was not informed the change need to adapt to the reversed operation as quickly as possible. The duration of the reversed operation was 3 min. A total of 13 pilots completed the test one by one.

2.3

Data Statistics

Data statistics were done by IBM SPSS 20.0 statistical software package. All test data are expressed by M ± SD (s). Paired t-test and the variance analysis of repeated measurement were used to analyze the group difference; P < 0.05 was set as the threshold value with a significant difference in statistics.

3 Results 3.1

Comparison of Performance in Different Operation

Individuals’ tracking deviation in normal tracking task was set as the base data for themselves. Performance scores of different tasks were the quotients of mean tracking deviation divided by base data. Therefore, the base scores were 1 for each pilot. The tracking deviation scores of first 6, 10, 15, 30, 60, and 180 s in reversed operation were calculated. Results of variance analysis of repeated measurement showed that tracking deviation among different phases was significantly higher than

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the base value (P < 0.01), see Table 1. The higher tracking deviation scores mean more disturbances by the reversed operation. The participants adapted to the reversed operation gradually after the 6 s, see Fig. 3.

3.2

HRV Change in Different Operation

HRV indexes of normal tracking task and reversed tracking task were compared with paired t-test. The results showed that heart beat rate (HBR) and LF/HF rate were significantly higher than that of reversed operation task, see Table 2.

4 Discussion For almost 100 years, various screening methods have been used to determine which individuals could perform well in pilot training. In military aviation, pilots needed to operate increasing complex aircraft system in a dangerous environment which could put them into an emergency situation at any time. Emergency coping ability was critical to success as a pilot, especially military pilots. Many mental attributes such as composed, calmness, good decision making and rapid reaction were all related to emergency coping ability. However, emotional stability was a most used concept in psychological test related to it. In aviation emergency situation, a pilot must keep calmness and operate correctly at the same time. So we think performance and psychological behavior should be combined together to evaluate emergency coping ability. Tracking test is the more typical psychomotor measure in aviation psychological selection system [6]. Deviation from target track was usually used to measure performance. In aviation, approaching and landing are typical tracking tasks which need accurate control. Localizer and glideslope deviation were used as performance variables [7].In this study, tracking performance has shown a sharp decline when the reversed operation started, especially in the first 6 s. Then tracking performance gradually recovered toward the normal level. So we concluded that the reversed operation had the most intensive effect on tracking performance in first 6 s. In this period, participants have found control failure and made an accurate judgement. After that, the adaptable operation began and the performance gradually recovered toward a normal level, even though most participants’ (10/13) performance were worst than that of base line after 180 s. According to the process, the sudden reversed operation made an emergency situation which lasted 6 s. Performance of first 6 s in operation change should be an index of emergency coping ability. Since the individuals have different normal performance level, the deviation from target track in reversed operation was reversed operation performance but was not the emergency coping ability. The ratio of the deviation from the target track in reversed operation in 6 s period and that of

Tracking deviation 1 Note *P < 0.05; **P < 0.01

Base line

10 s 4.29 ± 1.31

6s

5.37 ± 1.56

3.81 ± 1.32

15 s

Table 1 Tracking deviation among reversed operation and base line 30 s 3.00 ± 0.94

60 s 2.37 ± 0.84

180 s 1.73 ± 0.55

F value 72.429

P value 0.000**

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Fig. 3 Tracking deviation of different phases

Table 2 HRV change in different operation No. 1 2 3 4 5 6 7 8 9 Note *P

HRV HR RMSSD VLF LF HF LFNU HFNU LF/HF TOTAL < 0.05; **P
X > > rijl ¼ alij = auij > > = i¼0 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ; n  2 > X > > > riju ¼ auij = alij > ;

i 2 n; j 2 m

ð1Þ

i¼0

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 9 n  2 > X > > rijl ¼ 1=auij = 1=alij > > = i¼0 sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ; n    2 > X > > riju ¼ 1=alij = 1=auij > > ; 



i 2 n; j 2 m

ð2Þ

i¼0

h

 ¼ ðrij ðÞÞ ; rij ðÞ 2 The decision matrix obtained after standardization is D nm i rijl ; riju ; 0  rijl \riju  1. Similarly, a standardized scheme preference matrix

The Integration Design Parameters Selection Method …

h i  ¼ ðvij ðÞÞ ; vij ðÞ 2 vl ; vu ; P ij ij nm

311

0  vlij \vuij  1 is obtained for normalization

processing. Each scheme attribute vector is set to be normalized. n o n o (4) Remember rijl þ ¼ max rijl , riju þ ¼ max riju , j ¼ 1; . . .; m, then called the m 1in

1in

dimensional non-negative interval gray vector. r þ ðÞ ¼ ðr1þ ðÞ; . . .; rmþ ðÞÞ

ð3Þ

For the ideal optimal scheme vector, where, r þ ðÞ 2 ½rijl þ ; riju þ 

ð4Þ

The ideal optimal scheme vector represents the vector with the highest score of all design parameters under each attribute evaluation. The closer the attribute value and the ideal optimal attribute value in all schemes, the better the scheme is, the more important the design parameter is. (5) Set the interval sum xðÞ ¼ ½xl ; xu  and yðÞ ¼ ½yl ; yu , and then, the distance of the sum is defined as: dðxðÞ; yðÞÞ ¼

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðyu  xu Þ2 þ ðyl  xl Þ2

ð5Þ

The grey off coefficient of the ideal optimal scheme vector after normalization is defined as: min min dðrij ðÞ; rjþ ðÞÞ þ q max max dðrij ðÞ; rjþ ðÞÞ i

nij ¼

j

i

j

j

dðrij ðÞ; rjþ ðÞÞ þ qdðrij ðÞ; rjþ ðÞÞ

ð6Þ

Among them, q 2 ½0; 1 it is a resolution coefficient. (6) The grey off coefficient matrix is constructed from the grey off coefficient, denoted as n ¼ ðnij ðÞÞnm . 2

n11 6 n21 6 n ¼ 6 .. 4 . nn1

n12 n22 .. . nn2







.. .




3 n1m n2m 7 7 .. 7 . 5 nnm

ð7Þ

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(7) Remember the weight information of the attribute as w ¼ fw1 ; w2 ; . . .; wm g0 . In many cases, w it is completely unknown and can be solved by pressing the following formula. Remember that the sum of the deviation of the attribute values of the scheme si and the subjective preference values uj of the attribute values of the scheme is Di ðwÞ, Di ðwÞ ¼

m X j¼1

dðrij ðÞ; vij ðÞÞw2j

ð8Þ

Pn Pn Pm 2 Order i¼1 Di ðwÞ ¼ i¼1 j¼1 dðrij ðÞ; vij ðÞÞwj . Among them, Di ðwÞ it represents the total deviation between all objective preferences and their subjective preferences. Therefore, solving the problem of attribute weight vector is equivalent to solving the following optimization problem. 8 n n P m P P > > dðrij ðÞ; vij ðÞÞw2j < min Di ðwÞ ¼ i¼1

> > :

i¼1 j¼1

s.t.

m P

j¼1

wj ¼ 1; wj  0

ð9Þ

Can be obtained,

wj ¼

n X i¼1

!0 !1 11 n m X X A dðrij ðÞ; vij ðÞÞ @ dðrij ðÞ; vij ðÞÞ i¼1

ð10Þ

j¼1

8) The gray correlation degree n of design parameters w and evaluation indicators is calculated from grey correlation matrix and weight information. The gray correlation degree of the scheme vector si about the ideal optimal vector is: Zi ðr þ ðÞ; ri ðÞÞ ¼

m X

wj nij

ð11Þ

j¼0

According to the size of grey correlation, the design parameters are sorted, and the optimal design parameters are sorted by the degree of importance. The bigger the Zi ðr þ ðÞ; ri ðÞÞ, the better the program. If the attribute weight is known, it can be directly substituted into the calculation. Finally, according to the selection criteria, the design parameters are optimized. From the above steps, the selection process of integrated design parameters for equipment performance and testing is described in Fig. 2. As shown in Fig. 2, a decision matrix is constructed based on the correlation between design parameters and evaluation indicators, and a scheme preference matrix is constructed based on the subjective preferences of decision makers based on their expert knowledge and experience. Then, the decision matrix and the

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313

Evaluation Indicators Design Parameters Expert Knowledge and Experience

Decision Matrix

Programme Preference Matrix

Standardizating

Standardizating

Ideal Optimal Scheme Vector

Grey Association Coefficient

Weight Information

Grey Association Matrix

Design Parameter Selection Principle

Grey Association

Selection of Design Parameters Fig. 2 The integrated design parameter selection process of equipment performance and testing

scheme preference matrix are standardized. At the same time, we calculate the ideal optimal scheme attribute vector, the grey off coefficient matrix of the ideal optimal scheme, the calculated attribute weight vector, and the gray correlation degree of the schemes attribute vector about the ideal optimal vector. Finally, the scheme is sorted according to the grey correlation degree, the largest value is the optimal scheme, and the design parameters are selected according to the design parameters.

4 Conclusions It is the premise and foundation to carry out integrated design by combing equipment performance and testing-related design parameters and constructing integrated design parameter model. The method of selecting integrated design parameters in this paper not only considers the correlation between design parameters and design goals, but also considers various design constraints. Therefore, the selected design parameters are important and key, which lays a foundation for improving the comprehensive performance of equipment.

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References 1. Guanqin D, Jing Q, Guanjun L, Kehong L (2013) Environ street level evolution application basic model and international great association design. Chin J Aeronaut 26(2):456–462 2. Deng G, Qiu J, Liu G, Lv K (2013) A novel fault diagnos approach based on environmental street everuation. J Aerospace Eng 227(5):816–826 3. Zhang Q (2008) An objective approach to MADM with interest centres. J Common Comput 10(5):37–51 4. Wan SP (2009) Fusion method for interest number multi-nature. J Syst SciInform 7(2):119–128 5. Deng JL (1989) Introsion to grey system. J Grey Syst 1:1–24

The Integration Design Process and Method of Equipment Performance and Testing Guanqian Deng, Suqiong Kuang, Yingjie Lv, Guiyou Hao, Shaojun Qi and Pengjun Wang

Abstract By adopting the idea of parallel design, testing problem is considered at the beginning of the equipment development, and the integrated design of equipment performance and testing can make the equipment performance and testing to be optimized, and improve the comprehensive performance of the equipment. On the basis of combining the equipment design process, the paper gives the integrated design process of equipment performance and testing, introduces performance and testing-related design parameters in the equipment design objective function and constraint function, and establishes a multi-disciplinary optimization function. It provides support for the integrated design of equipment performance and testing. Keywords Equipment and methodology


Performance and testing
Integration
Design process

1 Introduction At present, a lot of equipment still use serial design methods, that is, the function and performance design are first carried out, and testing and maintenance issues are considered after the function and performance are verified [1–4]. The result is that although the functional performance meets the requirements, the equipment has problems such as poor reliability, long testing, and difficult diagnosis. It is costly to change the design at this time. Considering the performance and testing at the beginning of equipment development and adopting the idea of parallel design, developing the integrated design of equipment performance and testing is an effective way to solve the above problems. In this way, the performance and testing of equipment can be optimized.

G. Deng (&)
S. Kuang
Y. Lv
G. Hao
S. Qi
P. Wang Institute of Reliability Engineering, Beijing University of Aeronautics and Astronautics, Beijing, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_37

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2 The Integrated Design Process of Equipment Performance and Testing In order to carry out the integrated design of equipment performance and testing, the design process of equipment is first analyzed. It is roughly divided into the following stages: receiving the design task book, organizing the review, preparation before the design, design, detailed design, simulation and optimization, design output, and trial production of equipment. Each stage has its own design focus. The evaluation stage is mainly to review the task statement and technical conditions. The preparation stage before the design mainly conducts requirement analysis and prepares various standard specifications and technical documents. In the initial design stage, the product layout, structure division, function design, and measurement point selection are mainly carried out. At this stage, the integrated design of performance and testing needs to be planned. The integrated design of performance and testing is mainly carried out in the detailed design stage. The main designs include: module design, parameter design, and BIT design. The simulation and optimization stage mainly conducts finite element analysis, waveform simulation, testing simulation, design optimization, etc. The main output circuit diagram, structure diagram, software framework, diagnosis strategy and so on are provided at the main output stage. The design process of the combining equipment is roughly shown in Fig. 1. During the detailed design phase, further combining the integrated design process of equipment performance and testing is shown in Fig. 2. As shown in Fig. 2, equipment performance, testing and other requirement analyses are carried out based on the functional and structural requirements of the equipment; then, the performance and testing requirements are comprehensively weighed and analyzed, and the integrated design requirements of performance and testing are obtained. Then, the performance and testing design items are combed separately, and the design parameters are analysed. On the basis of this, a performance and testing design information model is established, and the performance and testing design parameters are determined according to the selection criteria of design parameters. Finally, the integration design and verification of performance and testing are carried out.

3 The Integrated Design Method of Equipment Performance and Testing The integrated design and optimization of equipment performance and testing refer to the optimal performance and testing of the system under given conditions, that is, the design of a system with the best integrated performance. This is a multi-objective optimization problem that is generally accompanied by optimal decision-making. The so-called optimal decision refers to the choice of the best option among the options available. For the integrated design of performance and

The Integration Design Process and Method of Equipment …

Accept Design Mission

Organizating the Review

Pre-design Preparation

Preliminary Design

Modify Design

Detailed Design Simulation and Optimization Meet Demand?

Design Output

Equipment Trial Production

317

Mission Statement Technical Conditions Demand Analysis Standard Specification Technical Paper Fault Information Product Layout Structural Division Functional Design Point Selection Parallel Design Module Design Parameter Design BIT Design Finite Element Analysis Waveform Simulation Test Simulation Design Optimization Structure Chart Circuit Diagram Diagnostic Strategy Software Framework

Fig. 1 Equipment design process

testing, the combination of performance and testing design parameters is selected as a scheme through the modeling of performance and testing-related design information and the selection principle of design parameters. Use efficiency and guarantee efficiency are used as evaluation indicators, which is the goal of optimization. The traditional performance and testing serial design method is one of the solutions. Because the scheme adopts serial design, it often takes into account the difference between the two, that is, the reuse efficiency and the protection performance, and it is difficult to achieve the optimal comprehensive performance at the same time. In fact, testing has a certain correlation with performance, and its design parameters also have a certain coupling relationship, which can be associated with related design parameters or variables. Taking missile weapons and equipment as an example, in order to improve the efficiency of the use of equipment, its

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The Requirements of Equipment Function and Structure Requirements Analysis of Performance Design

Requirements Analysis of Test Design

Other Requirements Analysis

Comprehensive Analysis of Design Requirements of Performance and Testing Integrated Design Requirements of Performance and Testing Analysis of Performance Design Project

Analysis of Test Design Projects

Performance Design Parameters

Testing Design Parameters

The Model of Design Information of Performance and Testing Design Parameters of Performance and Testing Integrated Design of Performance and Testing

Other Design Parameters

Selection Principles and Methods of Design Parameters Product Layout and Structure Function Division

Indicator Allocation of Performance Design

Indicator Allocation of Testing Design Comprehensive trade-offs

Integrated Design and Verification of Performance and Testing Equipment Development

Integrated Design Indicators of Performance and Testing Integrated Parallel Design

Fig. 2 Overall thinking of the integrated design of equipment performance and testing

availability indicators are highly correlated with reliability and fault detection rates, and the reliability of equipment is high, or failure can be diagnosed and repaired quickly. The equipment can have higher availability. Therefore, the reliability, fault detection rate, and other parameters can be combined to ensure the availability of equipment. Therefore, when the integrated design of equipment performance and testing is carried out, it is a multi-objective optimization problem, expressed in formula (1).

The Integration Design Process and Method of Equipment …

minf ðx; yÞ s.t: gðx; yÞ  0

319

ð1Þ

The multi-disciplinary optimization function is formed by the introduction of performance and testing-related design parameters in the objective function and constraint function. In the formula, the testing correlation function T(X, Y) is controlled by design parameters and coupling parameters. gðx; yÞ  0 is a constraint function, and Pfgðx; yÞ  0g  T is a constraint function for testing-related parameters. 8 min f ðx; yÞ  Tðx; yÞ > > < s.t. gðx; yÞ  0 > > : Pfgðx; yÞ  0g  T

or

8 1 min f ðx; yÞ þ Tðx;yÞ > > < s.t. gðx; yÞ  0 > > : Pfgðx; yÞ  0g  T

ð2Þ

4 Conclusions The integrated design of equipment performance and testing can avoid the difference and improve the overall equipment performance. In the preliminary design of equipment, the performance and testing are considered together, and parallel design is the best time for the integrated design of performance and testing. In the equipment performance and testing objective function and the constraint function to introduce performance and testing-related design parameters and solve, it is the key to achieve the integrated design of performance and testing.

References 1. Deng G, Qiu J, Liu G, Lv K (2013) A novel fault diagnoses approach based on environmental street evaluation. J Aerospace Eng 227(5):816–826 2. Traintaphyllou E, Sabchez A (1997) A sensibility analyze for home multi-critical decision-making methods. Decis Sci 28(1):151–194 3. Mareschal B (1988) Weights relations in multi-critical decision aid. Eur J Oper Res 33:54–64 4. Jian Ma, Zhiping F, Lihua H (1999) A subjective and objective adapted appliance to determine attribute weights. Eur J Oper Res 112:397–404

Design and Control of a Novel Pneumatic Soft Upper Limb Exoskeleton for Rehabilitation Qiaoling Meng, Zhongzhe Chen, Yingchen Li, Zhenji Tian, Zhiyu Wu, Lei Li, Xi Tang and Xiao Cui

Abstract The upper limb joints are easy to dislocate in the early stage of stroke. The protection of upper limb joints is particularly important in the early rehabilitation. This paper proposed a novel upper soft exoskeleton system, which can solve the risk of dislocation of the shoulder joint in the early stage of rehabilitation. The soft exoskeleton protected the shoulder joints through multi-chamber airbag mechanisms and designed a branches mechanism at elbow joints for the upper limb movement. The rehabilitation of the soft exoskeleton was the massage of upper limbs by filling and deflating the air chambers while the thin-film pressure sensors to collect and feedback the pressure of human epidermis. The kinematic analysis of the soft exoskeleton was established, and the substitution of data was done to verify the correctness of the mechanism of the soft exoskeleton. As a result, the experiments showed that the pressure sensor data was basically consistent with the theoretical values. The massage effect was remarkable, which was suitable for the rehabilitation of stroke patients at different stages. Keywords Soft exoskeleton


Stroke
Rehabilitation training
Pneumatic driven

Q. Meng (&)
Z. Chen
Y. Li
Z. Tian
Z. Wu
L. Li
X. Tang Institute of Rehabilitation Engineering and Technology, School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People’s Republic of China e-mail: [email protected] Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, People’s Republic of China Key Laboratory of Neural-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Shanghai 200093, People’s Republic of China X. Cui Department of Rehabilitation, Shanghai Changning Tianshan Traditional Chinese Medicine Hospital, Shanghai 200051, People’s Republic of China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_38

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1 Introduction Stroke has a high probability of disability [1]. Nearly 70% to 80% of patients are unable to live alone because of the disability among new stroke cases each year [2]. The results showed that interventionism rehabilitation of stroke patients with stable condition as early as possible can effectively alleviate the functional disability or reduce the disability rate of stroke to the greatest extent [3]. For the rehabilitation training of upper limbs in the early stage of stroke, medical staff often need to pay attention to the possible dislocation of shoulder joint caused by improper nursing. Meanwhile, with the recovery of patients, the muscle tension of affected limbs gradually increased and spasm occurred, patients are required to carry out passive stretching and joint activity training several times a day with the help of medical staff [4]. In the whole rehabilitation process of stroke patients, appropriate rehabilitation aids should be used as an important tool for training can not only ensure the safety and efficiency of rehabilitation training [5]. There are many intelligent rehabilitation robots for stroke patients nowadays. They are powerful and have good rehabilitation effects, but the high cost of treatment and the huge structure have been criticized. Moreover, many devices for stroke patients are huge and complex in structure [6]. Few stroke patients can purchase intelligent rehabilitation robots to continue home nursing training after leaving the hospital because of the size of the equipment and the high purchase price [7]. It is imminent to invent a modular composite multi-functional rehabilitation device, which is convenient to carry, cost-effective, and can provide corresponding protection and training for stroke patients in different rehabilitation stages [8]. This paper designs a soft exoskeleton system of functional rehabilitation and life support of stroke patients, aiming at reducing the risk of shoulder dislocation in acute rehabilitation, the difficulty of suppressing side spasm and joint movement during stroke spasm. By designing a soft exoskeleton rehabilitation training system with good flexibility, lightness, and comfort [9], we can provide necessary protective measures and diversified training modes in the process of stroke rehabilitation, so as to reduce the difficulty of rehabilitation for patients and promote the improvement of hemiplegic limb function of stroke patients. Through the kinematics analysis of shoulder and elbow, the scientific rationality of the design is verified. The experiment proves that the system achieves perfect function and has rehabilitation effects for patients.

2 Mechanism Design In terms of mechanical design, the following aspects were considered. Firstly, in order to prevent the dislocation of shoulder joint in patients with soft paralysis, the soft exoskeleton should provide necessary protective measures for shoulder joint. Secondly, it should be able to provide reverse traction for affected upper limb

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Fig. 1 Mechanical design model of soft exoskeleton

muscles to prevent spasm. Finally, it should be easy to wear, lightweight, and comfortable. The training position could be chosen freely without hindering the active rehabilitation training of the range of motion of the joints. The whole rehabilitation training device is composed of an airbag mechanism and a branch mechanism. The model is shown in Fig. 1. The airbag mechanism is divided into shoulder arm air bag and forearm air bag. On the one hand, it greatly improves the air permeability of the device. On the other hand, different ways of wearing can be selected according to the different needs of patients. As the core mechanism of the whole device, the airbag mechanism consists of shoulder air bag and forearm air bag. After the patient wears the device, the rehabilitation is carried out by the change of air pressure in the air bag. The airbag soft exoskeletons fully play the role of the support and protection in the process of training, especially for the shoulder joint. Shoulder airbag and forearm airbag design separately at the same time, including forearm airbag gas cavity block design, ensures the joints in patients with degrees of freedom. In rehabilitation training, the branch mechanism plays a connecting role in forearm air bag and shoulder air bag. It is composed of two strips and a rotating mechanism. The branch can be adjusted in the range of 0°–130°. Patients can receive rehabilitation training for elbow flexion at different angles according to their needs.

3 Kinematic Analysis In this paper, the D-H algorithm was used to determine the initial pose, and the coordinate system of each joint was successively established. According to the established joint coordinates and parameters, the D-H parameter table was obtained [10]. The plane joint coordinate system is established according to the D-H method as shown in Fig. 2. The D-H parameter table is shown in Table 1. Finally, the forward kinematics equation was established.

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Fig. 2 Coordinate system

Table 1 D-H coordinate parameters of plane joints

The joints

hi/(°)

a/(°)

ai/mm

di/mm

1 2 3

h0 = 0 h1 = 0 h2 = 90

0 0 0

0 0 0

d0 = 0 d1 d2

The graph coordinate system is the left-handed coordinate system,zi shaft with ai þ 1 joint axis reattachment, arbitrary pointing;xi shaft by zi and zi by the right-hand rule,d1 and d2 is the joint distance. Given the data of the joint variables and so on, the position and attitude of the end-effector relative reference coordinate system can be solved. The total transformation between the end coordinate system and the base coordinate system is: 2

C1 þ 2 þ 3 6 S1 þ 2 þ 3 0 A3 ¼0 A11 A22 A3 ¼6 4 0 0

S1 þ 2 þ 3 C1 þ 2 þ 3 0 0

0 0 1 0

3 Px Py 7 7 0 5 1

ð1Þ

Type: Px ¼ d1 C1 þ d2 C1 þ 2 þ d3 C1 þ 2 þ 3

ð2Þ

Py ¼ d1 S1 þ d2 S1 þ 2 þ d3 S1 þ 2 þ 3

ð3Þ

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where C1 þ 2 þ 3 and S1 þ 2 þ 3 represent cosðh1 þ h2 þ h3 Þ and sinðh1 þ h2 þ h3 Þ, respectively.

4 Control System The hardware architecture of this soft exoskeleton system was mainly composed of a main controller, a touch human-computer interaction screen, and four thin-film pressure sensors. In addition, four air pumps and four air valves were needed as the filling and deflating equipment of the soft exoskeleton. The communication between the human-computer interaction screen and the controller was established through the serial port. Four air pumps and valves were controlled by the controller. The surface pressure values of the pressure sensors subjected to exoskeleton compression were collected by the controller to form closed-loop feedback. If a certain part of the balloon exceeded the set pressure values, the corresponding valve would be opened to ensure the comfort and safety of the exoskeleton. The soft exoskeleton system is shown in Fig. 3. The first air pump was ventilated to the distal air bag and was controlled by the main controller to inflate. When the collected pressure value exceeded the set threshold, the first air pump was stopped. Corresponding gas valve was deflated,

Fig. 3 Pressure sensors and controller composed of the exoskeleton control system

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and then, the next air pump was inflated. As long as the steps above were repeated, a wave pneumatic massage would be formed from the far-end to the near-end.

5 Experiment In the experiment of pressure, the thin-film pressure sensor was placed in the area center where the experimenter contacted the soft exoskeleton. The pressure sensor cannot collect data when the inflatable program started. The study concluded that the main reason was that when the soft exoskeleton pressed the forearm, the pressure sensor would fall into the body tissue, and there was no stress point at all. Therefore, the pressure sensor was changed to place at the same point of the experimenter’s other hand. When the program was started, another experimenter pressed the sensor with its hand. The experimenter wearing the prototype felt the pressure of the two hands at the same position, when the forearm was pressed to the comfortable and urgent critical point, the force data of the pressure sensor was recorded. The data was acted as a critical point. The measured data range was approximately 120–150 mV. The data was converted to 0.25–0.35 N. The parameter received by MCU was 140 mV. Computer settings sent data every 0.1 s. The relationship between stress data and time was shown in Fig. 4. The values accorded with the stated value by comparing with the stated value. The results showed that the pressure on the human epidermis was within the comfortable pressure range and the pressure wave massage could be realized. The experiment prototype was shown in Fig. 5.

Fig. 4 Pressure acquisition data

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Fig. 5 Massage function experiment

6 Conclusion This paper designed a new soft exoskeleton system for upper limbs. The weight of exoskeleton was greatly reduced by using flexible air bag, which could protect the upper limbs of the hemiplegic side of patients. Through the detachable design of the branch, the connection and separation of the two parts of the balloon exoskeleton could be selected arbitrarily, and the modularization of the product was realized. And patients could choose different exoskeleton structures and training modes according to the rehabilitation stage to meet the needs of rehabilitation training. Acknowledgements This project was supported by the National Natural Science Foundation of China (61803265).

References 1. Dworzynski K, Ritchie G, Playford ED (2015) Stroke rehabilitation: long-term rehabilitation after stroke. Clin Med 15(5):461 2. Pavlovic AM, Pekmezovic T, Zidverc TJ et al (2016) Baseline characteristic of patients presenting with lacunar stroke and cerebral small vessel disease may predict future development of depression. Int J Geriatr Psychiatry 31(1):58 3. Chinese Society of Neurology (2017) Guidelines for early rehabilitation of stroke in China. Chin J Neurol 50(6):405–412 4. Deng Q, Luo ZC, Xia JC (2018) Application of rehabilitation equipment in recovery of limb function in patients with hemiplegia. Med Front 8(3):364 5. Prange GB, Jannink MJA, Groothuis-Oudshoorn CGM et al (2006) Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev 43(2):171–183 6. Zhang JL, Li L, Liu XX (2018) Development and application research of wearable exoskeleton robot. Mach Electron 36(3):1001–2257

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7. Wang LD, Liu JM, Yang G et al (2018) China stroke prevention and treatment report 2017. Chin J Cerebrovasc Dis 15(11):611–616 8. Li WF, Yu QH (2018) Effect of exoskeleton manipulator on functional recovery of upper limbs after cerebral infarction. Sun Yat-sen University 9. Xu XJ, Xu XL (2014) Application of pneumatic in rehabilitation of stroke. Chin J Rehabil Theor Pract 20(1):46–48 10. Tang G, Bai XL, Wang HS (2011) Human kinematics simulation based on joint coordinate system. J Comput Simul 28(8):1006–9348

Sketch Recognition and Interaction Design Based on Machine Learning Wei Feng, WanFeng Mao, Baiqiao Huang, Guanqun Zhang, Pengyi Zhang, Xing Li, Jian Su and Xingjun Yuan

Abstract Aiming at the problem of the high similarity of military graphic elements and low success rate of recognition when applied to sketched drawings, a form of sketch recognition technology based on deep learning algorithms is proposed, a human–computer interaction system for sketch drawing is developed on the basis of this technology, and also an improved design scheme for human–computer interaction is proposed. Experimental verification shows that such technology improves the success rate of military graphic element recognition and the efficiency of sketch drawing. Keywords Sketch drawing gence Machine learning





Human–computer interaction
Artificial intelli-

1 Introduction Man-machine-environment system engineering is a science which uses the method of system engineering and the theory of system science to correctly deal with the relationships between humans, machines and environments and to deeply study the optimal combination of man-machine-environment systems [1]. Human–computer interaction design is an important link for improving the task efficiency of systems composed of human and computer hardware and software, namely the “man-machine” part of man-machine-environment system engineering. With the rapid popularization of such hardware devices as intelligent terminals and the W. Feng
W. Mao
B. Huang (&)
P. Zhang
X. Li
J. Su
X. Yuan System Engineering Research Institute of China State Shipbuilding Corporation, Beijing, China e-mail: [email protected] G. Zhang China CNTC International Tendering Corporation, Beijing, China B. Huang Pilot National Laboratory for Marine Science and Technology, Qingdao, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_39

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successful application of many handwriting recognition systems, the automatic recognition of the handwritten content of operators has become the key to human– computer interaction design for such terminal devices. The development of artificial intelligence algorithms has been widely used in the field of handwriting recognition, such as handwritten Chinese character recognition and image recognition. Among them, there is a special kind of military application known as the “sketch board.” Sketch drawing is an important basic task of operational command. Commanders complete the drawing of tactical deployment maps by drawing operational sketches through handwritten input equipment. The key to sketch drawing is to capture the user’s input intentions based on sketch recognition [2], which requires that the graphic entities drawn by commanders should be recognized as standard entities in the military map gallery in order to improve efficiency. This is a typical problem of pattern recognition. Considerable research has been conducted on Chinese character recognition and image recognition, especially research into the introduction of deep learning algorithms for handwriting recognition [3, 4, 7] and facial recognition [5, 6], but it has not yet been applied to the military field. One important reason for this is that operational command requires rapid and accurate input. Another is that some military graphic elements are highly similar, which makes the accuracy of their identification insufficient. In this paper, a deep learning algorithm based on a convolutional neural network is applied to realize sketch-based graphic element image retrieval. The operation efficiency and detection accuracy of the application system can be effectively improved by quickly retrieving different hand-drawn abstract sketch elements, matching them with the standard element gallery and applying them thereafter. This provides a technical basis for the design of sketch drawing identification systems in the military field.

2 Sketch Recognition Processing Algorithms 2.1 2.1.1

Data Pre-processing Abstract Processing of Sketches

Compared with traditional color photographs, stroke order is the key information when drawing sketches on a touchscreen. The specific stroke orders of different sketches in the same category are different, yet the orders follow the general rules. The main outline is drawn first, then the details. On the basis of this rule, we added the principle that the earlier and longer the strokes, the more important they are. The two points are judged by formula (1) to determine the probability that the strokes will be removed. The ultimate purpose of data expansion is achieved by removing strokes of different proportions.

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pri ¼

1 aoi bli
e =e ; Z

s.t. Z ¼

X

331

eao =ebl

ð1Þ

i

In formula (1), oi is the order and li is the length of stroke i, a and b are two weights, respectively and Z is a normalized value. The removal of strokes leads to increasingly abstract sketches. While random schemes produce impractical sketch outlines, only earlier and longer strokes are kept. Our approach provides a simple and powerful way of providing data enhancement by adopting the unique attributes of sketches. 2.1.2

Deformation of Sketches

The aforementioned removal strategy is by its nature a data addition strategy which deals with essential changes in the abstraction of sketches to solve the problem of insufficient training data in existing sketches. In this section, another data addition strategy was introduced which takes advantage of another unique attribute of sketches compared with standard identification images, enabling the geometric information of the strokes to be used in training. In this strategy, partial and whole strokes in sketches are deformed, respectively. (1) Partial Stroke Deformation. To have partial strokes better reflect the characteristics of objects, the curvature of partial lines was added to make the sketches more vivid. Suppose that sketch S consists of a series of lines, i.e., S = fsgNi , (i is the stroke order of sketch S), and each stroke S consists of a series of line segments: S = fbgnj i , in which bj is the Bessel line, defined as formula (2):

bðtÞ ¼ ð1  tÞ3 p0 þ 3ð1  tÞ2 tp1 þ 3ð1  tÞt2 p2 þ t3 p3 ;

0t1

ð2Þ

p0 and p3 are the two endpoints of the Bessel curve. Choose two endpoints of each line segment as the backbone points of each stroke, and jitter these points through formula (3). p :¼ p þ 2;

s.t. 2  N ð0; rI Þ

ð3Þ

The Gauss standard deviation shall be the ratio between the distance between the two endpoints and the actual distance, which means a low probability of changing long and curved lines and a high probability of changing short and curved lines. After obtaining new points, we use the MLSs algorithm to connect these points and obtain new lines.

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(2) Whole Stroke Deformation. Along with partial stroke deformation, we also adopted whole stroke deformation to increase the data. First, the sketch outline is found by the convex hull algorithm, and the maximum or minimum points of the convex polygon coordinates are taken as the backbone points. Then, similar to partial stroke deformation, new points are recalculated and connected by formula (3) and the MLSs algorithm to generate a new outline. In the final algorithm, the two deformations are combined, with partial stroke deformation applied first, then whole stroke deformation.

2.2

Feature Extraction and Feature Quantization (Training in Sketch Retrieval Network)

“Feature extraction” refers to extracting the features of local image blocks or total graphs from hand-drawn sketches or standard image tags. “Feature quantization” can be used to assemble local features into global features and encode global features to make a description of the overall image. In general, good feature quantization makes the feature vector distance of non-similar figures larger while making similar figures smaller. (1) First, we needed to conduct classification training with a single sketch or standard image feature extraction network in order to give the network a better feature extraction effect and allow it to complete the basic function of extraction. (2) Hand-drawn sketches are composed of highly abstract discontinuous sparse lines, while standard image tags are composed of dense pixel points, making image matching more difficult. Our ultimate goal is to handle a similar sketch-image tag model. In this model, a common cross-domain feature space is mapped for matching between the features of sketches and natural images. The feature space closes the distance between the hand-drawn sketch and standard image tag and moves it further away from irrelevant tags, thereby realizing better training in cross-domain feature space mapping (as shown in Fig. 1) and a more efficient sketch retrieval function.

Fig. 1 Training in cross-domain feature space mapping

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In the public embedding space, we define similarity according to the squared Euclidean distance of sketch a and graphic image p: Dða; pÞ ¼ jjfh ðaÞ  fh ðpÞjj22

ð4Þ

fh ð:Þ is a cross-domain feature representation of the hand-drawn sketch and tag image. Dð:; :Þ is the Euclidean distance between sketch a and tag image feature p. According to our definition of similarity, we first use two twin neural networks to obtain positive/negative samples relative to the input sketch. As shown in Fig. 2, the two networks are actually the same, except one obtains positive samples and the other obtains negative samples. The two networks on the left and right have exactly the same network structure and share the same weight value W, and the input data is a pair of pictures (X1, X2). For two different inputs X1 and X2, the low-dimensional space results are respectively output as GW (X1) and GW (X2), which are obtained by mapping through a network. Then the distance EW between the samples is calculated using the two obtained output results; results with a distance greater than a certain threshold value are classified as negative samples, while samples with a lesser distance are classified as positive. Thus, for the input sketch, input tags trained many times are respectively stored in the positive and negative sample pools as input for training the triple neural network in the next step. Next, a triple neural network is used for feature extraction, of which the three inputs are a positive sample, negative sample and sketch respectively. As shown in

Fig. 2 Twin neural network used to distinguish positive and negative samples

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Fig. 3, we used a triple ranking loss function to constrain this feature representation. Finally, the hand-drawn sketch can be closer to the tag image of the positive sample and further from the representation image of the negative sample, i.e., Dðfh ðaÞ; fh ðp þ ÞÞ\Dðfh ðaÞ; fh ðp ÞÞ. The network structure is shown in Fig. 3. The final triple loss function is as follows: L ¼ maxð0; m þ jjfh ðaÞ  fh ðp þ Þjj22  jjfh ðaÞ  fh ðp Þjj22 Þ

ð5Þ

where m is the threshold value between positive sample sketch distance and negative sample sketch distance. If the threshold can allow the positive samples and negative samples to be sorted correctly, the triple network will not suffer from losses; otherwise, the value of the loss function will fall between 0 and 1. The final loss function is defined as follows: X min Li þ kWðhÞ ð6Þ i

where i is the number of triple training sets, h represents the parameters of the neural network and the norms of such parameters, and WðhÞ represents the norms of the regularization parameters. Minimizing the loss function shortens the distance between the sketch and positive image patterns while enlarging the distance between the sketch and negative image patterns. When there is sufficient training data, the depth model will eventually produce a satisfactory ranking representation.

Fig. 3 Sketch retrieval training network structure

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2.3

335

Feature Matching (Sketch Retrieval Network Test)

“Feature matching” involves measuring the similarity between the two types of image and further matching to obtain the score, thereby realizing image retrieval. To match cross-domain features between a sketch and tag image using the convolutional neural network described above, it is first necessary to import the trained network model into a retrieval system. When a user inputs a hand-drawn sketch, the system will extract and match the sketch and tag image features according to existing experience and return the retrieval results (Fig. 4). Body dimensions data of crews are obtained by human body measurement. And database is established and used to guide height of navy equipment control console, angle of inclination of screen and layout design of upper function key or button on console so that designed equipment is suitable for most people. Besides, adequate operation space is provided for operators in terms of placement design of equipment. Particularly, maintenance space shall be considered in advance and maintenance space outside equipment shall be considered in equipment placement, Navy equipment is mostly placed in a narrow cabin. Thus, priority shall be given to consider the constraint relation between space of cabin and physical dimensions of personnel.

Fig. 4 Feature matching and feedback between sketch and image

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3 Interactive Design and Test Results In the experimental analysis, four relatively similar standard image tags were selected and a positive and negative training pool established. After training in the established model, six experimenters randomly drew sketches of four kinds of tag patterns. For each tag, 10 sketches of different forms were drawn, including different sizes, directions (including inversion) and colors. A total of 60 sketches were generated for each tag pattern. The correct recognition times are shown in Table 1. The test statistics show that the success rate of correct tags directly given by the model is about 70%. Considering the randomness of such attributes as the variety, high similarity and sketch direction of military graphic elements, this recognition rate is acceptable in the preliminary study. In order to further improve the efficiency of human–computer interaction, we input a matching tag list according to matching degree for the user to choose. When the user finishes drawing a sketch at a specific position on the screen, a matching result selection list will pop up next to that sketch in its current position with a limit of 5 results. After the user selects the standard tag, the sketch will be replaced in the original position. Also in the above experiment, the matching list of tags for selection is used to replace the original results with the highest matching degree, and the test results are shown in Table 2. The average success rate of expected results in the list is about 87.92%, thus further improving the efficiency of human–computer interaction. Table 1 Accuracy rates of directly given correct tags

Table 2 Accuracy rates of top five correct tags in matching list

Experimenter 1 Experimenter 2 Experimenter 3 Experimenter 4 Experimenter 5 Experimenter 6 Mean accuracy (%) Total accuracy

Experimenter 1 Experimenter 2 Experimenter 3 Experimenter 4 Experimenter 5 Experimenter 6 Mean accuracy (%) Total accuracy

Tag 1

Tag 2

Tag 3

Tag 4

7 6 8 7 9 5 70 70%

6 8 5 7 7 8 68.33

8 8 6 4 9 9 73.33

7 6 7 6 8 7 68.33

Tag 1

Tag 2

Tag 3

Tag 4

8 9 9 7 9 8 85 87.92%

8 10 9 8 10 9 90

9 9 8 8 10 10 90

9 8 9 8 10 9 88.33

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4 Conclusion This article presents a form of sketch recognition technology based on an artificial intelligence algorithm, further proposes a fast plotting method for image tags based on this technology and studies the interaction of this technology in system application. After preliminary tests, combined with the trained algorithm model and appropriate interaction design, the success rate of sketch recognition can reach an acceptable level. By improving human–computer interaction, the success rate of sketch recognition is further improved, which provides a technical basis for the design of sketch-based human–computer interaction systems.

References 1. Shengzhao L (1993) Human-machine-environment system engineering theory and its significance in productivity development. In: Progress in human-machine-environment system engineering research, vol 01, pp 2–13. Beijing Science and Technology Press, Beijing 2. Li-Sa Z, Zheng-Xing S, Ruo-Hong Z et al (2004) A method of graph-based composite sketchy graphics recognition. J Comput Sci 31(4):147–150 3. Xiaoqing M, Qingbing S (2017) Handwritten signature verification algorithm based on LBP and deep learning. Chin J Quantum Electron 34(1):23–31 4. Lili G, Shifei D (2015) Research progress on deep learning. Comput Sci 42(5):28–33 5. Hinton GE, Qsindero S, The YW (2006) A fast learning algorithm for deep belief nets. Neural Comput 18(7):1527–1554 6. Hu G, Yang Y, Yi D et al (2015) When face recognition meets with deep learning: an evaluation of convolutional neural networks for face recognition. In: Proceedings of the IEEE international conference on computer vision workshops, pp 142–150 7. Song Z, Yu R (2015) Research on the classification of handwriting number based on deep learning. J Chongqing Technol Bus Univ 32(8):49–53

Development and Application of Test Software of Fine Operation Ability of Directional Motion Weicai Tang, Yi Xiao, Fenggang Xu and Chunhui Wang

Abstract The test software of fine operation ability of directional motion, which is used for handle control, is independently developed on the basis of the C++ program development platform for the discrete-type operation missions such as the spatial manipulator teleoperation, crane, excavator, etc. It aims to test the fine operation ability of directional motion of the operators, including the astronaut. The reliability and validity test results of the software indicate the software has good internal consistency reliability and retest reliability and can well differentiate the operators who have the training experience of manipulator teleoperation and the operators who are not trained. In addition, there is a significant correlation between the test and the operator’s age. The fine operation ability increases progressively with the increase of the age. Keywords Fine operation ability Reliability Validity





Directional motion
Test software


1 Preface The fine operation ability is defined as the operator’s ability for the fine motion or performing the fine mission with hands or manual operation tools. It is the comprehensive reaction of the muscle strength for controlling fine motions, coordination and accuracy of motions, the psychological activities of sensory perception, attention, spatial perception, etc. [1–3]. There are various types of fine operation tasks in space station construction and lunar landing exploration, including manual-control rendezvous and docking and on-orbit manipulator teleoperation. Even the lunar rover also carries a manipulator

W. Tang
Y. Xiao (&)
F. Xu
C. Wang Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Center, Beijing 100094, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_40

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for sampling and transporting soil and rock and orientating and placing instruments, etc. [4]. Now for the manned space mission, the manual-control rendezvous and docking, manipulator teleoperation and other spatial teleoperation missions have high requirements on the astronaut’s fine operation ability to the handle. There were also some teleoperation accidents caused by the astronaut’s faults in the fine operation stage [5]. The fine operation ability to the handle is mainly classified into the control ability of discrete motion operation and the control ability of continuous motion, wherein, the discrete motion can be classified into fixed-point motion and directional motion according to different motion tracks, and the continuous motion can be classified into regular motion and irregular/random motion. Now, the fine operation ability is mainly measured by taking the irregular motion tracking mission as the measurement tool at home and abroad. The irregular motion tacking mission controls the target of the random motion in a certain range with the handle and mainly investigates the operator’s speed perception, continuous control and reaction abilities to the moving target [6–9]. The software targets to the discrete operation missions such as the spatial manipulator teleoperation, crane, excavator, etc. The missions are characterized by the motion is discrete and the motion speed and direction can be controlled by handle, and the motion can stop at any time during the process. It has low requirements on the operator’s speed perception, continuous control and reaction abilities but high requirements on the distance perception ability, fine control ability and handle operation stability, etc. In the actual mission, particularly in the process of transferring the operation target in a large scale, the motion path is limited to a certain extent because of the external environment, obstacles, etc. [10]. Thus, designing the assessment paradigm for the fine operation ability of the directional motion of the spatial teleoperation mission is helpful for monitoring and training the fine operation ability of the operators, such as the astronaut, etc. The similar test method of the fine operation ability of the directional motion was invented as early as in the 1990s. The line marking mission in the children motion development test which is made by S.E.Henderson and D.A.Sugden is a test of the operation control ability of direction motion. It mainly tests the control and coordination abilities of hand muscles [11]. The operator is tested by using a pencil to draw lines along the pattern edges in the middle-blank part of the double-side line. The number of the times when the operator touches the edge line in the marking process is used as the assessment criteria of the test. Compared with the line marking mission, graph copying more focuses on the coordination and cooperation of the hand motion and visual perception. Researches prove the pupil’s line marking and graph copying abilities are significantly relevant to the child’s school record. The higher the line marking and graph copying abilities are, the higher the child’s school record will be [2]. In addition, NASA also developed the similar test mission in the manned space flight experiment. Kathy Jackson and Gibson, et al., used mazes and probes to test the influence imposed on the motion sensory skill by long-time weightlessness. The operation time of adjacent holes and the total time are acquired by inserting probes into every hole (inflection point) of the maze in order and used as the assessment indexes of the test [12, 13]. There are also relevant

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researches for the operation control ability of directional motion and its application in the aerospace industry [14–16]. Duoduo Hui, Wendong Hu, et al., from the Fourth Military Medical University developed a computerized test system of mental motion ability, which has been used for recruiting commercial airline pilots [17]. The target control of the spatial manipulator teleoperation, crane, excavator, etc. mainly tests the operator’s ability of controlling the handle by hand. Thus, the test software of fine operation ability of directional motion based on handle control is developed according to the relevant test principles of the line marking above, etc. and combining with the handle control method and requirements of distance perception and handle precision control indexes in the operation process of the mission.

2 Software Structure and Composition Based on the line marking mission, the test replaces the pencil with a handle to control the ball to move on the track of a certain width. The test software is developed and realized on the basis of the C++ language and comprises of five modules: operation control module, path design module, test plan design module, data collection output module and interface representation module. (1) Operation control module There are eight operation directions for the handle, i.e., up, down, left, right, left up, left down, right up and right down. The operation direction of the handle corresponds to the motion direction of the ball. The handle operation load is shown by the ball motion speed: the ball speed is 0 when the handle operation load is 0; the ball motion distance in a unit time is 1 pixel when the handle operation load is not higher than half of the maximum operation load; and the ball motion distance in a unit time is 2 pixels when the handle operation load is higher than half of the maximum operation load. (2) Path design module There are four motion tracks of the ball, which comprise of common lines and curves, and it operates from low difficulty to high difficulty in order, as shown in Fig. 1. Path 1 comprises of simple horizontal lines and vertical lines; path 2 comprises of horizontal lines and up and down inclined lines of 45°; path 3 comprises of horizontal lines and up and down semicircles; and path 4 comprises of horizontal lines and up and down inclined lines of 60°. (3) Test plan design module Referring to the actual condition, alarm information prompts for the impact between the ball and the track are increased, i.e., when the ball moves close to the track edge, the ball speed decreases and keeps at the rate of 1 pixel in one unit time. During the ball motion process, when it detects the ball touches the track boundary, the ball turns red and alarms (as shown at the right side of Fig. 1).

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Fig. 1 4 kinds of test paths

To meet the demand of controlling the motion in different directions, two motion directions are set in the same path, i.e., the motion from left to right and the motion from right to left. Handle buttons are used for switching the motion direction. For ensuring the test can sufficiently reflect the operator’s fine operation ability of direction motion, test time pressure is applied to the operator, the test time of each round is limited as 60 s, and it automatically goes to the next round when the mission is completed or not completed in the limited time. Experiments verified all operators could complete the mission in the limited time, and the limit time was enough for them. The test results were not significantly influenced by prolonging or shortening the experiment time. (4) Data collection output module The sampling frequency of the software internal timer is 1000 Hz and meets the demand of collecting the data of handle operation and ball motion. The output frequency of the actual data record is 10 Hz. The collected data include coordinates of the ball circle center, operation loads of two dimensions of the handle, ball motion distances, ball motion time, impact times between the ball and track, etc. The data automatically save and output after the end of each test. (5) Interference representation module The software comprises of a user logon interface, a test instruction interface and a test interface, wherein, the test interface comprises of three information parts, i.e., the test path drawn according to the information of the path which is selected by the user on the logon interface, real-time position of the ball and real time after the test starts.

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3 Application of Evaluation Software 3.1

Experiment Flow

The test mainly comprises of three steps as follows: (a) the operators respectively gets familiar with the four paths with the left hand and right hand; (b) the operator carries out the operation test of the first round, i.e., controls the ball to move from right to left with the convenient hand, and then controls the ball to move from left to right with the other hand on each path; (c) the operator carries out the test of the second round, i.e., controls the ball to move from right to left with the inconvenient hand, and then controls the ball to move from left to right with the convenient hand on each path. The ABBA experiment order is used for controlling the learning effects of the left and right hands. There are 60 s in total for the motion control in each direction on each path. The operator has to complete the experiment within the designated time and try best to reduce the impact times between the ball and the wall.

3.2

Result Analysis

The experiment results mainly comprise of the touch times between the ball and the wall during ball motion, motion distance and motion time, and the speed control and precision control ability in the operator’s handle control are comprehensively tested. The index of the touch times between the ball and the wall is used as the primary assessment index, and the normalized motion distance and normalized motion time are used as the secondary assessment standard, and the sum of the three is used as the performance Q of the operator’s fine operation ability of directional motion. Thus, when the touch times between the ball and the wall are same, the operators’ motion control abilities can be reflected by the normalized motion distance and time. The lower the Q value is, the higher the motion control ability will be. Q ¼ Touch times þ

Motion distance Motion time þ S T

Wherein S and T are normalized constants. (1) Normality test K-S nonparametric test was carried out to the test index Q of the fine operation abilities of directional motion from left to right of the left hands and right hands and the test index from right to left of 84 operators who are graduated from undergraduate colleges or above, and the normal distribution results are shown in the following table:

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Table 1 Normality test Test projects

~x  s

Dominant hand, move from left to right Dominant hand, move from right to left Non-dominant hand, move from left to right Non-dominant hand, move from right to left Total test indicator

1.99 2.29 1.89 2.08 8.24

± ± ± ± ±

0.88 1.00 0.80 0.97 3.12

KS-Z

p

1.242 1.341 1.012 0.979 0.901

0.091 0.055 0.258 0.293 0.392

Table 1 indicates all significance P values are higher than 0.05; thus, the results subject to normal distribution. (2) Reliability The reliability mainly comprises of internal consistency reliability, retest reliability, etc. The analysis of internal consistency reliability was carried out to the test indexes from left to right and the test indexes from right to left (four items in total) of the left hands and rights of the 84 operators above so as to test the internal consistency reliability of the test and the result of the internal consistency reliability coefficient (Cronbach’s Alpha) is 0.876, and also all items have significant correlations at the level of 0.01, which verifies the test has good internal consistency reliability. Two months later, 27 operators were retested for the correlation analysis of the results of the two tests, and the Pearson correlation coefficient was calculated as 0.804, the significance P < 0.001, i.e., there is the significant correlation. The result verifies the test has good retest reliability. (3) Content validity The content validity shows the sampling appropriateness of the project for the content or behavior range to be tested. Single-factor analysis of variance was carried out to 24 operators who have been trained for manipulator operation and 60 operators who do not have the similar operation or training experience, and the result shows the Leven statistics is 0.227, p = 0.635 > 0.05. Thus, there is the homogeneity of variance of data. The test index Qnot trained of the fine operation ability of the operations who are not trained is 8.87 ± 2.98, and the test index Qtrained of the operations who have been trained is 6.67 ± 2.97, F(60, 24) = 9.411, p = 0.003, i.e., the fine control ability of direction motion of the operations who have been trained is significantly higher than that of the operators who are not trained. Thus, the test software can well differentiate the operators who have different operation control levels and has good content validity. (4) Age factor analysis The correlation analysis carried out to the test index of the fine operation ability of directional motion of the 55 operators from the 84 operators above and the operators’ ages got the Pearson correlation factor of −0.844, p = 0.002, which reflects

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Changing Curve of Test Indicator-Age

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10 8 6 4 2 0 18

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the test index of the fine operation ability of directional motion and the age are in significant negative correlation (as shown in Fig. 2), i.e., the fine control level increases with the increase of age. It conforms to the result that all fine motion abilities of the individual continuously develop with the increase of age, which is got by Beilei Li, et al. from Beijing Normal University [2].

4 Conclusion The researches above prove the test software of fine operation ability of directional motion has good test reliability and validity, well reflects the operator’s control ability of direction motion and provides good reference for selecting the operators of spatial manipulator operation, crane control and other industries. Acknowledgments This work is supported by the Equipment Advance Foundation of National Key Laboratory, No. 614222201060317. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of China Astronaut Research and Training Center. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Zhao WF (2012) Advancement in the fine motor control ability of the elder. Chin J Gerontol 32(15):3348–3349 2. Li BL, Lin L, Dong Q et al (2002) The development of fine motors and their relations to children’s academic achievement. Acta Psychologica Sinica 34(5):52–57

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3. Liu PP, Wang JL (2013) The meaning and measurement of the fine motion of hand. Med J Chin People’s Armed Police Forces 24(7):639–640 4. Tang GJ, Zhou JY, Zhang B et al (2011) A survey of teleoperator rendezvous and docking technology. Manned Spaceflight 17(2):38–44 5. Shayler D (2000) Disasters and accidents in manned spaceflight. Springer 6. Manzey D, Lorenz B, Schiewe A et al (1995) Dual-mission performance in space: results from a single-case study during a short-term space mission. Human Factors: J Human Factors Ergon Soc 37(4):667–681 7. Manzey D, Lorenz B, Poljakov V (1998) Mental performance in extreme environments: results from a performance monitoring study during a 438-day spaceflight. Ergonomics 41 (4):537–559 8. Fowler B, Bock O, Comfort D (2000) Is dual-mission performance necessarily impaired in space? Human Factors: J Human Factors Ergon Soc 42(2):318–326 9. Seidler RD, Reuter-Lorenz PA, Mulavara AP et al (2014) Spaceflight effects on neurocognitive performance: extent, longevity, and neural bases (NeuroMapping) 10. Forman RE (2011) Objective performance metrics for improved space teleroboticstraining. Massachusetts Institute of Technology 11. Henderson SE (1992) Motion assessment battery for children[M]. Psychological Corporation, London 12. Fowler B, Meehan S, Singhal A (2008) Perceptual-motor performance and associated kinematics in space. Hum Factors 50(6):879–892 13. Summerlin LB (1977) Skylab, classroom in space 14. Wang RZ (2009) The review of the effectiveness of various psychological tests in European and American pilot selection. J Civil Aviat Flight Univ China 20(3):17–21 15. Wu GC (1995) Assessment of flight ability from cognitive psychological point of view. Chin J Aviat Med 6(2):120–124 16. WEI HC (2013) The application research of psychomotor ability in civilaviation pilots selection. The Fourth Military Medical University 17. Hui DD, Li XJ, Wen ZH et al (2014) Development and application of psychomotor ability test system. Comput Technol Dev 24(12):180–182

Research on Key Technology to Underwater Robotic Arm Shang Huan, Suqin Wang, Xu Han and Jianzhi Bi

Abstract To meet requirements of training astronauts for space task on ground, robotic arm working underwater is researched. Methods The solution to the underwater robotic arm is proposed by research on the robotic arm’s major structure, drive and control, neutral buoyancy design, sealing, corrosion resistance, and so on. Conclusion Through the modeling and simulation, underwater robotic arm owned rational structure, stable control system, and has the ability to cover the working space. Furthermore, underwater sealing means has passed the test. Consequently, the method to develop underwater robotic arm is feasible and reasonable. Keywords Underwater


Robotic arm
Neutral buoyancy

1 Introduction During the mission of the space station, with the support of the robotic arm, astronauts need to carry out a series of space tasks, such as extravehicular inspection, material transfer, and on-orbit maintenance [1]. And this demands the astronaut to wear extravehicular spacesuit for precise operation in the weightless environment. So, the prior ground test and training are indispensable. It is a safe and economical way to conduct the underwater simulation training in the neutral buoyancy simulator with a space module model and underwater robotic arm [2]. NASA, for example, has established the neutral buoyancy laboratory (NBL). The model of the international space station is placed in a giant pool, 61 m long, 31 m wide, and 12 m deep, to train the astronauts to get familiar with the procedures and characteristics of a space mission (Fig. 1) [3, 4]. S. Huan (&)
X. Han
J. Bi China Astronaut Research and Training Center, Beijing 100094, China e-mail: [email protected] S. Wang North China Electric Power University, Beijing 102206, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_41

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Fig. 1 NASA neutral buoyancy laboratory

Generally, the large underwater experiments need the collaboration of divers [5]. Especially, long-term underwater training, the demand on divers is bound to increase significantly. It is a better way that researching and developing the underwater robotic arm replace the divers to support underwater training. This not only greatly reduces the demand on divers, but also improves the training efficiency. China has established the neutral buoyancy pool which is 23 m in diameter and 10 m deep for the SZ-7 extravehicular training task. Next, China will pay attention to the space station mission. The underwater robotic arm must be applicable to the underwater environment. It is the typical combination of robot technology and underwater engineering technology. This paper focuses solution on the key question such as body structure, drive and control, neutral buoyancy, underwater sealing, and corrosion resistance.

2 Body Structure The big robotic arm of the space station adopts a two-section symmetric structure with seven degrees of freedom. Its shoulder and wrist can be interchanged. The arm can switch base point by end-effector capturing adaptor, which can crawl on the outside of the station body to expand the operating area [6]. Compared with NBL, current our pool size is too small to contain the entire space station model. It has to be separated into multiple sections or their combination to meet the training demand. Thus, the configuration of the underwater robot arm is not restricted to space station big arm, but can be optimized to save the cost according to the training requirement. The body structure of the underwater robotic arm is designed as shown by Fig. 2. It adopts a double-arm-rod folding structure with 6 degrees of freedom and a mobile base. The arm rods can be folded or unfolded to cover the working areas at the near end and far end. The pitch shoulder joint and yaw shoulder joint and the pitch elbow joint together provide 3 degrees of freedom to determine and shift the terminal positions. The pitch wrist joint, yaw wrist joint, and

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Pitch wrist joint

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Pitch elbow joint

Arm

Yaw wrist joint

Roll wrist joint Pitch shoulder joint

Yaw shoulder joint Mobile base

Fig. 2 Structure of the underwater arm

Fig. 3 Location of the underwater robotic to different duty

roll wrist joint together provide 3 degrees of freedom to determine and adjust the terminal attitude. Six degrees of freedom can meet the demand for position and attitude adjustment. Compared with the robotic arm of the space station, the underwater robotic arm saves a roll joint on the shoulder and an end effector, which simplifies the overall structure. The mobile base is made of stainless steel for the lower arm center of gravity so as to increase its stability and can resist the instant impact of 5000Nm. The mobile base can be fast moved and leveled in the pool, in order to walk to expand the working area. Different module-combination models correspond to different base points, as shown in Fig. 3. With the coverage simulation of the working area, the underwater robotic arm has to be 11 m long in total, thus, the single arm rod can be set as 5 m long. The underwater robotic arm performs the task with the end

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Fig. 4 Astronaut on the arm Tool rack Grab bar

End effector

Foot restraint

Arm

effectors on the wrists. During the training, the astronaut wears the underwater extravehicular spacesuit and stands on the foot restraint which is provided with grab bar and rotary tool rack to help the astronaut operation. The foot restraint is locked on the end effectors of the wrists with the fast installation interfaces. The underwater robotic arm adjusts the astronaut’s position and attitude by calculating and driving corresponding joints. The astronaut can also independently adjust the yaw and roll attitude by, respectively, pedaling the left pedal and right pedal of the foot restraint, as shown in Fig. 4.

3 Drive and Control Generally, the robotic arm is driven by hydraulic pressure and motor, wherein the hydraulic drive comprises of oil pressure and water pressure. The drive of the oil pressure has the advantages of high torque, compact structure, and good rigidity but is easy to leak, will pollute the water quality, so it cannot be used. Although the drive of the water pressure does not have the problem of water quality pollution, the water medium has low viscosity and is easier to leak than the oil medium, which causes the processing precision of the water pressure control valve block cannot be met in China at present, so that the driving of the water pressure shall not be used either. The motor drive technology is mature and has high control precision; therefore, the underwater robotic arm shall be driven by a motor.

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Calculation of Driving Force

In the process of work, the underwater robotic arm can keep neutral buoyancy owed to balance the effect between gravity and buoyancy by overall structure design. Thus, the self-movement of the underwater robotic arm mainly has to overcome the water resistance. Among the six joints, the pitch shoulder joint and yaw shoulder joint bear the maximum force, followed by the elbow joint and then the three wrist joints. At first, it is considered as the limiting case when the two arm rods completely unfold in parallel and rotate around the yaw shoulder joint at a uniform speed with no load. At this time, the underwater robotic arm can be simplified as a round pipe of which the length is L and diameter is b, around an end point to do a uniform rotation motion. Let the speed is x, take the length of its microelement dx, distance rotation axis for x. The tangential water resistance around the rotation axis is dM, and then it can derive the water resistance torque (Fig. 5). 1 F ¼ qV 2 SCf 2

ð1Þ

1 dF ¼ qV 2 bdxCf 2

ð2Þ

dM ¼ xdF

ð3Þ

Substitute Eq. (2) into Eq. (3), then: 1 dM ¼ qx2 x3 bCf dx 2 ZL

ZL dM ¼

M¼ 0

1 2 3 b qx x bCf dx ¼ qx2 L4 Cf 2 8

ð4Þ

ð5Þ

0

Wherein, the resistance coefficient Cf is the function of the Reynolds number Re. With the look-up table method, the cylinder drag coefficient Cf = 1.2. b = 0.3 m and L = 11 m are taken for the pipe. The end shift motion is 200 mm/s, i.e., x = 1.04°/s,

Fig. 5 Calculation model to robotic carrying astronaut

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then M = 218 Nm. The formula above show that the water resistance torque will significantly increase with the increase of the arm length and angular velocity. With the astronaut as load, the arm increasing water resistance torque is: 1 Ma ¼ LFa ¼ qx2 L3 SCf 2

ð6Þ

The astronaut wearing the underwater spacesuit is equivalent to be a cylinder of 1.8 m long and 0.83 m diameter. Its resistance area is 1.5 m2, then Ma = 396 Nm is calculated out. Thus, the shoulder has to overcome the water resistance torque of 614 Nm. In the same way, the water resistance torque of the elbow joint is 252 Nm. For the water resistance torque of the wrist joints, the pitch wrist joint which is the biggest is taken. The maximum angular velocity 3°/s and L = 3.5 m (from the astronaut head to the wrist pitch axis) are plugged into formula (5), and then the water resistance torque is calculated out as about 50 Nm. In addition, according to the acceleration 5 mm/s2 to shift, the rotational inertia of the shoulder joint is 1.0  105 kgm2, and the driving torque is about 46 Nm; thus, the driving torque of the shoulder joint is about 660 Nm. Given one-time margin, the driving torque of the shoulder joint is about 1320 Nm, and the driving torques of the elbow and wrist joints can be derived in the same way.

3.2

Joint and Control

The underwater robotic arm joints is mainly composed of the drive motor, reducer, brake, sensor, sealing device, shell, and so on. Overall encapsulation is designed for structure. Flanges are used for connecting movement components and fixed components of the joints, and the hollow shaft of the motor is used for distributing the power and signal lines, which avoids the lines winding during motor rotation. The joint output shafts are directly connected with the arm rod for torque transmission. The multi-joint connection of the wrist is designed as Fig. 6 [7]. Based on the

End effector

Integrated driver

Arm Joint

Fig. 6 Assembled wrist joint

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mission planing

3D simulate path planing

image process

shoulder camera

current sensor shoulder yaw controller

elbow camera wrist camera

robotic handle

data process

host

CAN bus

switch

Ethernet

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shoulder pitch controller

underwater

rotate sensor position sensor

leak decetor

elbow pitch controller

depth sensor

wrist yaw controller

position sensor

wrist yaw controller

current sensor

wrist roll controller

rotate sensor

...

position sensor

Fig. 7 Architecture of control system

calculation of joint driving torque underwater, it is the low-speed high-torque driving mode [8]; therefore, frameless torque motor and RV reducer are adopted to drive the shoulder and elbow joints to improve the shift rigidity and precision. Wrist joint drive adopts frameless torque motor and a harmonic reducer to realize smooth attitude adjustment. The joint is embedded with current sensor, speed sensor, and absolute position sensor, forming the current, speed, and position three closed-loop PID control system, to achieve the purpose of quick dynamic response and precise position servo. The control system is divided into the above and below water parts, as shown in Fig. 7. Among them, the overwater part is mainly the control host, responsible for acquisition, task planning, path planning, 3D movement simulation, real-time image display, and recognition; the underwater part is mainly embedded joint controller and its sensor. CAN bus is used for control communication and Ethernet is used for video data of the arm camera.

4 Design of Neutral Buoyancy The neutral buoyancy status means that the buoyancy and gravity of the underwater robotic arm are equal in water, and the center of buoyancy and the center of gravity basically coincide, which is the basis of its precise motion control. However, the center of gravity of the underwater robotic arm changes with the working attitude.

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Fig. 8 Cross section of arm

For making the center of buoyancy always coincide with the center of gravity, it must independently balance each component (except the base), particularly the arm rod and joints. The arm rod is made of titanium alloy with a thickness of 8 mm to achieve the optimal ratio of mass to rigidity. The inner wall of the rod is filled with solid buoyancy material to keep it in a neutral buoyancy status (Fig. 8). A routing pipeline is reserved at the center. The solid buoyancy material has low density (0.2 g/cm3), high strength, low water absorption, corrosion resistance, non-toxic, and harmless. It does not contaminate the test environment. Its buoyancy follows uniform distribution along the axis, then:     ðqTi  q0 Þ  p  ðR2  r 2 Þ  l ¼ q0  qf  p  r 2  r02  l

ð7Þ

    ð4:5  1Þ  R2  ðR  0:008Þ2 ¼ ð1  0:2Þ  ðR  0:008Þ2 r02

ð8Þ

Wherein, R is the outer diameter of the arm rod, r is the inner diameter of the arm rod, and r0 is the outer diameter of the hollow pipe. Take R = 150 mm, then r = 142 mm. Substitute them into formula (7), then r0 = 99.7 mm. The routing space is sufficient, and the design is feasible. Since the joint drive adopts frameless motor, the external diameter of the joint can be precisely adjusted to achieve self-balancing in water. For example, accurately estimated the wrist joint, the integrated driver is 50 kg, the length l = 500 mm, and the hollow pipe diameter r0 = 30 mm. According to Eq. (9), R = 210.5 mm, it is more than the motor diameter and less than 250 mm, indicating that the design is feasible. Other joints can also follow this method for self-balancing.   ðqTi  q0 Þ  p  R2  ðR  0:008Þ2  l þ 50 ¼ q0  p  ðR2  r02 Þ  l

ð9Þ

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5 Underwater Sealing and Corrosion Resistance The underwater robotic arm has a strict demand for the sealing technology. Neither allowing water to enter the internal joint, nor allowing the media to overflow and contaminate the pool. At first, ceramic bearings which are corrosion resistant, abrasion resistant, anti-electromagnetic, and oil-free self-lubrication are used for the joints. Secondly, the technology of combining static seal and dynamic seal together is used. The double O-ring is used for the static seal in the joint end covers. The joint output shafts are dynamically sealed by the new lip-type ring. The test data indicate the new lip-type sealing ring can reduce the friction torque and keep constant pressure in the sealing chamber, compared with other seal rings. The static seal and dynamic seal are in redundancy with two seals. Thirdly, the joint sealing chambers are aerated to maintain the internal and external pressure balance fourthly, sensors are embedded in the joints to monitor the leakage at real time and ensure sealing reliability. kept water temperature 28–30 °C, pH 7–7.8, free chlorine is less than 0.6 mg/L, the arm corrosion rate has three factors: dissolved oxygen, hardness, and chloride ions. Among them, dissolved oxygen is the most important factor [7]. Therefore, the corrosion resistant can be reinforced from the aspects of material selection, structural design, processing craft, and electrochemical protection. The optimal materials for the underwater robotic arm are titanium and stainless steel, both of which are highly passivable. The passivating film is in a stable status and has resistance to chloride erosion. For economic considerations, the base of the robotic arm is made of 316 L stainless steel to reduce the arm center of gravity and increase its stability, while the arm and joints are made of TC4 titanium alloy to ensure its motor dexterity. Since metal corrosion always starts from its surface, it is important to keep surface in the best status through structure and craft optimization so as to effectively avoid mechanical stress, solid particle sedimentation, electric couple corrosion, and others, which is to maintain the equipment performance.

6 Conclusion and Expectation The robotic arm can cover different working spaces with its six degrees of freedom, mobile base and double-arm-rod folding asymmetric body structure. Based on calculating equivalent model of the water resistance, the driving force and driving structure of each joint are determined. The three-closed-loop PID control of current, speed, and position is used for fast dynamic response and precise position servo. The robotic arm always is in the neutral buoyancy status, by whole arm self-balancing design. Static seal and dynamic seal are combined with the leakage monitor to guarantee the reliability of the underwater seal. The anti-corrosion capability of the robotic arm is improved by selected material property and craft. Modeling and simulation results show that the arm has a rational structure, stable

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control system, and has the ability to cover the working space. Due to the assistance and support of the arm, the underwater experiment and training efficiency are to be significantly improved. Acknowledgements This work is supported by the Basic Research Subject of National Key Laboratory of Human Factor Engineering, No. SYFD170051803.

References 1. Wertz JR, Larson WJ (1999) Space mission analysis and design. Kluwer Academic Publishers, Dordrecht 2. Huan S, Deng H (2011) Design and implementation of the interface system for a space flight training-simulator based on CAN bus[J]. Space Med Med Eng 24(5):361–365 3. Liang B, Xu W (2017) Space robotics: modeling, planning and control. Tsinghua University Press, Beijing 4. Dempsey R (2017) The international space station operating an outpost in the new frontier. NASA-SP-2017-634 5. Moore SK, Gast MA (2010) 21st century extravehicular activities: synergizing past and present training methods for future spacewalking success. Acta Astronaut 67:739–752 6. Wang Y (2018) Space robotics. Beijing Institute of Technology Press, Beijing 7. Han L (2018) Project design on underwater robotic arm. Shanghai Aerospace Systems Engineering Institute 8. Xu W, Bin L, Xu Y (2011) Survey of modeling, planning, and ground verification of space robotic systems]. Acta Astronaut 68:1629–1649

A Portable Variable Stiffness Unpowered Aided Exoskeleton Design Luoqin Yu, Kai Wang and Tianning Chen

Abstract Long-term and long-distance walking, especially weight-bearing walking, can lead to a series of health problems, such as physical decline, muscle fatigue, and even muscle injury. In order to provide precisely walking support for users, our team studied the movement characteristics of normal people’s unilateral lower limbs from transition phase to support phase, the kinematic position relationship and energy conversion relationship of the human hip joint in different gait periods, and the internal cam mechanism is designed accordingly. Considering the individualized demand of user’s walking aid, a variable stiffness energy storage mechanism is designed, which can be adjusted according to user’s height. Through EMG test, it is proved that the mechanism has a good effect of assisted walking. The energy storage mechanism of unpowered aided exoskeleton is mainly composed of cam and roller follower. Compared with traditional energy storage mechanisms such as connecting rods, they are smaller in size and easier to wear, which provides some useful ideas for the human-friendly design of unpowered exoskeleton. Keywords Variable stiffness mechanism


Aided exoskeleton
Wearable
Energy storage

1 Introduction Since the 1990s, engineers have been designing a machine to make people walk more lightly and simply [1, 2]. Many people need to carry out long-term and long-distance walking in their daily work and life. For example, nurses, urban sanitation workers, pipeline maintenance personnel, and military personnel are walking or weight-bearing walking for most of their working time. Busy work and long-term walking will greatly affect their work efficiency and quality of life [3]. L. Yu (&)
K. Wang
T. Chen School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_42

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Meanwhile, with the development of social economy and people’s constantly deepening of nature exploration, higher requirements for man’s walking ability are put forward in the exploration of natural resources and outdoor exploration activities. Moreover, the power of the elderly’s leg muscles also is declined. Clark et al. [4] found that the muscle strength of the elderly at 70–79 years old decreases at a rate of about 3% per year, so that they are prone to encounter with accidents such as falls and fractures due to instable support of legs. Long-term and long-distance walking often leads to decline in physical power and other symptoms such as muscle fatigue. Long-term muscle fatigue is also the most important cause of muscle tissue damage. Serious muscle damage may even lead to other consequences such as kidney failure [5]. The damage made to human body due to muscle tissue damage is irreparable. In this paper, by studying the working characteristics of thigh muscles and the position changes of hip joints of the human body during walking, an aided mechanism which can periodically store energy and release energy is designed. Its stiffness and dimensions can be adjusted individually according to the user’s need. In order to verify the feasibility of the design of this unpowered hip-joint exoskeleton mechanism, an experiment of the aided walking effects for the unpowered hip-joint exoskeleton was completed.

2 Muscle Work in Human Walking and Design of Unpowered Aided Exoskeleton 2.1

Exoskeleton Principle Analysis Based on Human Walking

Normal walking of human body can be regarded as movement in the sagittal plane which has the characteristics of periodicity and repetition. A gait cycle refers to the process from one heel touches the ground to the same heel touches the ground again [6]. The design of the driving mechanism is based on the different movement stages shown in Fig. 2. That is to say, the designed energy storage mechanism can store the negative work done by the human body in the back support phase and release it in the front swing phase and partial transition phase to assist the human body in doing work. The energy storage mechanism adopts the design of combining roller translating follower disk cam and spring. In the swing phase, the hip joints of the human body rotate to store the negative work done by the muscles in the compressed spring through thigh bar. When the tiptoes push off the ground to start walking, walking assistance is realized. The rotation angle of hips in the coronal plane of the human body is mainly considered. According to the range of the rotation angle of hip joints in normal walking process of people, the maximum

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Fig. 1 Energy storage and boosting process of energy storage mechanism

backward rotation angle of hip joints reaches 21° in back support phase; the maximum forward rotation angle of hip joints reaches 32° in transition phase; hip joints reach a vertical state at the beginning and end of the back support phase, as shown in Fig. 1.

2.2

Exoskeleton Design of Unpowered Aided Exoskeleton

Based on the studies of movement anatomy of the human body, the design scheme of a kind of unpowered aided walking hip-joint exoskeleton is proposed, as shown in Fig. 1. The exoskeleton can follow movement of human body synchronously through the belt and the bandage below knee joints. The energy storage mechanism can adjust the stiffness according to user’s needs to achieve the most suitable walking assistance. The length of thigh bar and the degree of bandage tightness can meet the needs of different body conformations. As shown in Fig. 2, the functions of each part are as follows: ① The belt is used to fix exoskeleton waist and can be adjusted according to body conformations of different people; ② The energy storage mechanism with a rotating axis located at the hip joints of the human body can periodically store and release energy in the process of walking to achieve the purpose of walking assistance; ③ The stiffness adjustment knob with stiffness adjustment threads, through which different users can adjust the stiffness of the energy storage mechanism according to their own needs by adjusting the knob to achieve the purpose of optimizing assistance; ④ The thigh bar with length and dimensions that can be adjusted to the appropriate length according to different

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Fig. 2 Diagram of exoskeleton wearing and thigh bar size for different height groups

Fig. 3 Bionic design of knee joint mechanism and the slip and movement of knee joint

heights; ⑤ The knee joint rotor which can keep smooth movement between thigh and shank and the exoskeleton; ⑥ The shank band which makes the bottom of the exoskeleton always fits the shank and avoids relative movement between them. As shown in Fig. 1, the length of the thigh bar can be adjusted to fit users of different heights. As shown in Fig. 3, the bionic design of the rotor at each knee joint ensures that the exoskeleton of the user will not hinder the relative movement of the thigh and shank during the walking process so as to walk smoothly. The design of the rotor at the knee joint is a gear meshing mechanism. Compared with the shaft hole matching structure, it has characteristics, such as large range of transmission power, high efficiency, long service life, and safe and reliable operation, and can simulate the actual movement of the knee joint.

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3 Calculation and Determination of Cam Configuration In the course of human walking, the cam follower may instantly jump out of cam profile due to large inertia force, which may cause run-out and lead to vibration. In order to avoid such situations, we need to find out the relationship between cam profile and spring stiffness and design the energy storage mechanism based on this input condition. According to the cam-rolling follower mathematical model, as shown in Fig. 4, it is assumed that the damp of the cam can be neglected in the process of walking and the shafting of the cam is absolutely rigid. Given: K1 is the stiffness of the maintaining spring, m is the equivalent mass of the follower system, K2 is stiffness of the follower system (mainly including cam profile and contact stiffness of the follower and stiffness of the follower itself that can be measured by experiment), and H is the stroke of the follower; Given: walking cycle of human body T and the maximum angle between two legs in walking (rotation angle of cam operating stroke)r, assuming that the thighbone rotates uniformly in the sagittal plane with the hip joint as its center in the walking process of the human body, the cam speed can be determined as x ¼ 2r=T. Suppose Dh is the increment of cam rotation angle. It is stipulated that the follower conforms to the following motion law: X ¼ X ðtÞ. If vibration of the follower is not taken into consideration, suppose the displacement of Point A is X 0 and the following relational expression can be obtained according to the principle of equilibrium of statics: K1 x0 ¼ K2 ðy  x0 Þ, that is: X0 ¼

Fig. 4 Mathematical model of cam-rolling follower

k2 y k1 þ K 2

ð1Þ

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Fig. 5 Analysis of the motion law of the follower

If vibration is taken into consideration, suppose the actual displacement of the follower is X, X 0  X, then the differential equation with the follower is € ¼ k2 ð X 0  X Þ mX

ð2Þ

As shown in Fig. 5, when vibration is not taken into consideration, the motion function of the follower is X 0 ¼ X 0 ðtÞ and take any three consecutive points to make X 0 ¼X 0 0 ¼ 2 1 . Since them meet the condition that tmid  t1 ¼ t2  tmid ¼ Dt, then X_ mid 2Dt

Dh ¼ xDt,


x 0 X_ mid X20  X10 ¼ 2Dh

ð3Þ

Similarly, speed of Point A and Point B, midpoints of the two sections, can be X 0 ¼X 0 obtained, respectively, Speed of Point A: X_ A0 ¼ midDt 1 , Speed of Point B: X 0 ¼X 0 X_ B0 ¼ 2 mid , whereupon accelerated speeds of midpoints can be derived from Dt

Eq. (3):  x 2
X 0  XA0 0 0 €mid X ¼ ¼ B X10 þ X20  2Xmid Dh Dt

ð4Þ

Similarly, when vibration is taken into consideration, the actual displacement x ðX2  X1 Þ also meets X_ mid ¼ 2Dt €mid ¼ X

 x 2 Dh

Substitute Eq. (4) into Eq. (2), m 0 Xmid ¼ Xmid þ

ðX1 þ X2  2Xmid Þ


x 2 Dh ðX1

0 þ X2  2Xmid Þ ¼ K2 Xmid  Xmid

m  x 2 ðX1 þ X2  2Xmid Þ K2 Dh

ð5Þ
ð6Þ

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Substitute it into Eq. (1), Ymid ¼

K1 þ K2 0 Xmid K2

ð7Þ

Therefore, the cam profile y ¼ yðhÞ can be obtained by numerical method through (5), (6) under the condition that the movement law of the follower X ¼ X ðtÞ, m, K1 , K2 , x, H and r are known.

4 Electromyography Test of Unpowered Aided Exoskeleton 4.1

Introduction of Experimental Process and Method

The instrument used in the experiment is BIOPAC MP150 wireless electromyogram acquisition module, and the subjects are male college students in good health. They did not have alcoholic food or take other drugs within 24 h before the test. The subjects participated in the test wearing the exoskeleton prototype under good rest, which is convenient for test data comparison, as shown in Fig. 6. The test time was around 4:00 p.m. Before formal test, the test task was introduced to the subjects to ensure that the subjects understood the test operation correctly. In the test, when

Fig. 6 Exoskeleton experiment of subjects who wearing unpowered aided exoskeleton

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Table 1 Testing plan of walking assist effect Control Group C Experimental Group T1 Experimental Group T2 Experimental Group T3

Without wearing the unpowered aided exoskeleton, the subjects stood still for 10 s, walked at a constant speed for 20 s, and recorded the data Wearing unpowered aided exoskeleton, rotate stiffness adjusting knob, adjust the stiffness to minimum, stand still for 10 s, walk uniformly for 20 s, record data Wearing unpowered aided exoskeleton, rotate the stiffness adjusting knob, adjust the stiffness to the medium, stand still for 10 s, walk uniformly for 20 s, and record the data Wearing unpowered aided exoskeleton, rotate the stiffness adjusting knob, adjust the stiffness to the maximum, stand still for 10 s, walk uniformly for 20 s, and record the data

subjects were wearing exoskeletons, surface electromyographic signals from rectus femoris and biceps femoris of their lower limbs in walking state were collected. The experimental plan is as shown in Table 1. Among surface electromyogram indexes of the four limbs, the lower the integrated EMG value is, the lower the degree of fatigue will be; if the root-mean-square value increases, the degree of muscle fatigue also increases. In this experiment, integrated electromyographic (IEMG) value and root-mean-square (RMS) electromyographic value are adopted as indexes. In the test process, the sampling rate of EMG signals is 2000 Hz. After filtration, the average integrated electromyogram (IEMG) value and root-mean-square (RMS) amplitude of the corresponding process were obtained.

4.2

Experimental Results and Analysis

For data in Experiment 1, the average integrated electromyographic (IEMG) values were used as the indexes. The experimental results are shown in Fig. 7.

Fig. 7 Experimental data results of IEMG

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In the results of rectus femoris experiment: The root-mean-square electromyographic value of Experimental Group T1 of wearing exoskeleton with minimum stiffness was 13.4% (P < 0.05) lower than that of Control Group C; the root-mean-square electromyographic value of Experimental Group T2 of wearing exoskeleton with medium stiffness was 21.5% (P < 0.05) lower than that of Control Group C; the root-mean-square electromyographic value of Experimental Group T3 of wearing exoskeleton with maximum stiffness was 32.6% (P < 0.01) lower than that of Control Group C. In the results of biceps femoris experiment: The root-mean-square electromyographic value of Experimental Group T1 of wearing exoskeleton with minimum stiffness was 9.6% lower that of Control Group C; the root-mean-square electromyographic value of Experimental Group T2 of wearing exoskeleton with medium stiffness was 17.28% (P < 0.05) lower than that of Control Group C; the root-mean-square electromyographic value of Experimental Group T3 of wearing exoskeleton with maximum stiffness was 22.3% (P < 0.01) lower than that of Control Group C. With the increase of the stiffness of the energy storage mechanism, the average integrated electromyographic (IEMG) values decrease and the muscle fatigue decreases progressively, which shows that in the adjustable range of spring stiffness, with the increase of the stiffness of the energy storage mechanism, the unpowered hip-joint exoskeleton plays a significant role in improving walking assistance. For data in Experiment 2, the root-mean-square (RMS) values were used as the indexes. The experimental results are shown in Fig. 8. In the results of rectus femoris experiment: The root-mean-square electromyographic value of Experimental Group T1 of wearing exoskeleton with minimum stiffness was 32.1% (P < 0.05) lower than that of Control Group C; the root-mean-square electromyographic value of Experimental Group T2 of wearing exoskeleton with medium stiffness was 46.4% (P < 0.05) lower than that of Control Group C; the root-mean-square electromyographic value of Experimental Group T3 of wearing exoskeleton with maximum stiffness was 60.7% (P < 0.01) lower than that of Control Group C.

Fig. 8 Experimental data results of RMS

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In the results of biceps femoris experiment: The root-mean-square electromyographic value of Experimental Group T1 of wearing exoskeleton with minimum stiffness was 17.2% (P < 0.05) lower than that of Control Group C; the root-mean-square electromyographic value of Experimental Group T2 of wearing exoskeleton with medium stiffness was 31.0% (P < 0.05) lower than that of Control Group C; the root-mean-square electromyographic value of Experimental Group T3 of wearing exoskeleton with maximum stiffness was 58.6% (P < 0.01) lower than that of Control Group C. With the increase of the stiffness of the energy storage mechanism, the root-mean-square (RMS) values decrease and the muscle fatigue decreases progressively, which shows that in the adjustable range of spring stiffness, with the increase of the stiffness of the energy storage mechanism, the unpowered hip-joint exoskeleton plays a significant role in improving walking assistance.

5 Conclusions There is recyclable energy in the human body during walking. Through the periodic action of cam and spring, a part of the recyclable energy is stored on the spring assembly contacting the cam. Through periodic energy storage and release of the spring, it assists thigh muscles to complete leg lifting, so as to reduce the energy used for muscle contraction and lower the energy loss during walking. Through a mathematical algorithm, the dimensions of cam follower were obtained, and it is verified in the experiment. The new wearable unpowered lower limb walking-assistance exoskeleton studied in this paper is an important form of walking-assistance exoskeleton, and it has the following advantages. Firstly, compared with traditional powered exoskeleton, the unpowered exoskeleton needn’t to control and track joints (in real time), so that it has inherent stability and can complete periodic walking without any external control system; secondly, it does not need additional power source from the outside in the walking process, which avoids multiple times of charging caused by insufficient endurance of exoskeleton due to its own weight; thirdly, unpowered exoskeleton has a more affordable price than those with extra power, so that it is easier to popularize, thus bringing enormous social benefits and application prospects. For example, in the military field, it can reduce the loads on soldiers’ muscles and joints and help soldiers go further; in the medical field, it can help doctors reduce the fatigue of muscles and joints caused by longtime standing for surgeries; in addition, the unpowered joint exoskeleton can also be well applied in sports and daily life of the elderly. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of Xi’an Jiaotong University. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

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References 1. Grabowski AM, Herr HM (2009) Leg exoskeleton reduces the metabolic cost of human hopping. J Appl Physiol 107(3):670 2. Zoss A, Kazerooni H (2006) Design of an electrically actuated lower extremity exoskeleton. Adv Robotics 20(9):967–988 3. Chen Y et al (2014) Analysis of physiological stress and fatigue in simulated weight-bearing walking. Chin J Occup Diseases 32(8):584–587 4. Clark BC, Taylor JL (2011) Age-related changes in motor cortical properties and voluntary activation of skeletal muscle. Curr Aging Sci 4(3):192–199 5. Wang J (2014) Study on the characteristics of surface electromyographic signals in human back loading. Dissertation, Tianjin University of Science and Technology 6. Zhang J et al (2017) Human-in-the-loop optimization of exoskeleton assistance during walking. Science 356:1280–1284

Expressway Vehicle Management System Based on Vehicle Face Recognition Chan Zhang, Lijian Deng, Qicai Du and Weiming Deng

Abstract Facing the problems in the current situation of highway vehicle management, this paper demonstrates the construction of a big data platform based on the vehicle face recognition technology, and uses the technology such as vehicle feature intelligent identification, big data service platform data, platform and external system docking, in order to provide efficient solution for expressway managers, and finally achieves the effect, which pay low cost for the fee of the highway vehicle management, and improves the efficiency and accuracy of the inspection of traffic management.







Keywords Vehicle face recognition Expressway vehicle management Big data

1 Background The number of Chinese motor vehicles in recent years is greatly increasing with the fast development of national economy and the improvement of people’s living standards. The fast extension of expressways and inter-city highways provides great convenience for people’s transportation but also brings many new problems for the expressway traffic management, for example, the toll dodging by on-road cards, fake plates, and cloned vehicles. The problem of violating the traffic regulations on the expressway is also serious. These problems cause a huge loss to the expressway business income as well as a series of hidden dangers of public security order and traffic safety [1]. Under the background that Guangdong province has realized the one toll collection net of province-wide networking of provincial expressways, the mainline toll stations and marking stations which are at the entrances and exits but not the provincial boundaries of the expressways are not used. When the vehicle travels in the province, the driver only needs to get one card and pay once. The payment sum C. Zhang
L. Deng
Q. Du
W. Deng (&) Special Operations Academy of PLA, Guangzhou 510500, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_43

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increases when the vehicle traveling distance on the expressway increases. Thus, driven by interests, the numbers of the toll-dodging vehicles, fake accident vehicles, oil stealing vehicles, smuggled vehicles, intentional traffic violation vehicles, and other suspected vehicles increase, which increases the management difficulty, and these suspected vehicles often have fake plates, no plates, or covered plates. The traditional system based on plate identification cannot solve the problem of identifying these vehicles. The article aims to provide an effective solution for expressway management by establishing the big data platform based on the vehicle face identification technology for all expressways in the province.

2 Current Condition of Toll Collection Facilities of the Expressway Generally, the expressway follows the overall mode that collects the toll and split according to the actual path. It is classified into mobile payment with stop and mobile payment without stop according to the driver’s payment methods which are used as the classification standards. (1) Manual semiautomatic toll collection based on IC card (MTC) The basic flow of the manual semiautomatic toll collection is as follows: manual-type judgment/automatic-type judgment, issue the card by people (or self-service) at the entrance, the camera captures the plate number, verifies the card at the exit, verifies the plate, calculates the toll, manually collects the toll, computer management, video monitoring, and detector check. (2) Electronic toll collection (ETC) without stop based on RFID technology The basic flow of ETC is as follows: the ETC side unit antenna RSU and vehicle-carried unit OBU information communicate to get the information of the vehicle type, entrance, exit, time, etc., and then fast toll collection is realized. The ETC technology which doesn’t use cash for payment increases the pass-through efficiency, reduces the cash management cost, makes the fund recharging and settlement ways be more flexible, and is fast popularized by cooperating with banks. HD mounts and lane HD capturing and plate identification facilities of the main line are additionally arranged at the exit and entrance of each toll station and service area with the unified plan, and the lane-level anti-toll dodging and intercepting function is realized. Although the expressway operation management departments have built a great quantity of video image mount equipment for assisting toll collection and operation management, it is still simple application stage which is based on the plate number retrieval, the entrance and exit mounts, and the mainline mount of the expressway, respectively, belong to the toll collection network and monitoring network but are

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not networked for deep application. With the depreciation of the mount equipment and the variation of the light environment, everyday more than 2-million images in xx province have errors in plate identification and cannot effectively display the vehicle traveling track. The toll-dodging vehicles just dodge the toll by fake plates, no plate, or covered plates and often disappear in the huge number of plates which are wrongly identified, which make the toll collection management personnel and inspectors don’t know how to start.

3 Big Data Platform of Vehicle Face Identification The big data platform of vehicle face identification (hereinafter referred to as the platform) creates the one net for the big data analysis of vehicle face identification through the intelligent analysis and secondary identification of characteristics of all vehicles to the images of the vehicles passing through the expressway image mounts in the province, including the entrance mounts, exit mounts, and mainline mounts. The platform effectively and fast retrieves the brand, color, type, etc., of the vehicle without depending on the plate number and can fast find the suspected vehicle which influences traffic safety or dodges the toll, collect the process and trace information of the suspected vehicle, and consolidate the chain of evidences of toll dodging and influences on traffic safety so as to help the expressway operation, toll collection, and inspection departments pursue the toll dodged by the vehicle. In addition, the platform can also provide evidences of the vehicle and driver who is intentional for traffic violation, fake accidents, drug trafficking, or smuggling to the public security department for effective strikes; thus, the platform can greatly increase the expressway management level [2].

3.1

System Structure

The platform is constructed in two stages, namely the provincial center and road section. The data (images of vehicles passing through the exits, entrances, HD mounts and service area mounts, and pipelining) collected by the front end of the platform are classified, identified and saved, and converted into text data in the stage of road sections, and then sent to the provincial operation center for storage [3] (Fig. 1).

3.2

Logic Structure

The logic structure of the platform system comprises a resource tier, a collection tier, a service tier, and an application tier from bottom to top [4].

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Fig. 1 Big data platform of vehicle face identification

The resource tier mainly comprises all front-end monitoring equipment and mount data collection equipment at the entrances and exits of the toll stations and road sections. It is the perceptual tier of the system and used for capturing road vehicle data. The collection tier mainly comprises the input and storage of front-end data, carries out identification, characteristic extraction and data cleaning and conversion to the passing vehicle information and vehicle image information, and stores the vehicle identification data. The service tier mainly encapsulates the system service and provides data service capabilities to the upper tier, including data retrieval capability, characteristic comparison service, authority management service, data analysis, and computing service. The application tier mainly provides all types of business which conform to expressway demands and encapsulates according to actual demands, including the judgment of on-road cards, analysis of fake plates, analysis of toll-dodging vehicles, etc.

3.3

Storage Structure

The images of the vehicles passing the mounts of the platform are stored in the characteristic identification servers of road section vehicles (if any characteristic identification server of road section vehicles doesn’t have enough space, a separated storage server shall be configured). For saving the investment cost of system construction, the provincial monitoring center doesn’t store the images of the

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vehicles passing the mounts but uses the image URL to quote the images stored in all road sections and calls the image data of all characteristic identification servers of road section vehicles through the network to display the image. Varied by the docking modes of the mount data, the images of vehicles passing the road section mounts in the characteristic identification subsystems of road section vehicles are stored in two ways as following: (1) Directly docking with the mount cameras: after being obtained from the mount cameras, all images are stored in the characteristic identification servers of vehicles, and only the mount image data within 90 days are reserved. The system automatically and circularly deletes the mount image data 90 days before. (2) Getting the image data through the HD mount system: for reducing the construction cost of system storage and ensuring the system can fast check the mount images, the road section identification servers only save the mount data within 30 days. If the system has to access the historic image data 30 days before, the image data stored in the HD mount system is quoted and accessed with the image URL address.

3.4 3.4.1

Core Technology Intelligent Identification Technology of Vehicle Characteristics

The identification technology of vehicle characteristics based on GPU accelerated deep study technology is the core technology of the identification big data platform of vehicle faces. It structures the vehicle image data through vehicle detection, vehicle positioning, type classification, characteristic extraction and identification and comparison, converts image data into the structured data which can be inquired by one key, and cracks the problem that the traditional expressway business only depends on the plate identification but cannot accurately and fast lock the targeted vehicle and personnel activity [5]. The GPU accelerated deep study technology is based on the training of massive vehicle model data and is characterized by fast identification speed, high accuracy, rich identification contents, etc.

3.4.2

Data of Big Data Service Platform

The big data service comprises the core technologies of a distributed file system, a distributed database, a distributed message queue, a distributed search engine, a stream computing framework, etc. The distributed design provides a linear transverse extension capability and provides a reliable, expandable, and fault-tolerant computing system for massive data processing.

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The distributed file system HDFS uses an effective distributed algorithm to distribute data access and storage in a great number of servers and distributes the accesses in all servers of the cluster besides provides the reliable multi-backup storage. It is characterized by self-repair, dynamic capacity expansion, high-throughput capacity, low construction cost, etc. The distributed database HBase is a distributed and column-oriented open-source database. Different from the common relation database, HBase is applicable for non-structured data storage and is characterized by the storage index of massive data, high inquiry and analysis efficiency, optimized storage space, etc. The distributed message column Kafka is a distributed publishing and subscribing message system of high-throughput capacity. It can process producers and consumers’ data models and simplify the system programming model. The Kafka message column provides message persistence with the 0(1) disk data structure and can keep longtime stability of the storage of terabytes of messages and support 100 thousands of messages per second. The distributed search engine Elasticsearch is a Java search engine server based on Lucene. The reverse-order index sorting mode of Elasticsearch provides the search capability of top speed and high throughput as well as the tier-level search and eye-catching display of hit and supports multiple output formats (including ML/XSLT and JSON formats). It is easy to install and configure [6]. The system uses the Storm open-source stream computing framework for the stream computing processing. Storm is a distributed, expandable, and fault-tolerant real-time computing system. Based on the Storm framework, the developer can easily develop the application for continuous stream data processing. Storm is characterized by simple programming model, supporting all programming languages, high fault tolerance, reliable and fast message processing, horizontal expansion based on the thread, progress, and server.

3.4.3

Relation Between the Platform and External System

(1) Relation with the mount system: the platform gets the images of the vehicles passing through the entrances and exits of the toll collections system of road sections and images captured by the mainline HD mount systems and service area mount systems and converts them into the basic data sources of the platform. Thus, the image quantity and quality determine the performance and utilization effect of the platform. (2) Relation with the toll collection system: the platform gets some pipelining fields (pipelining number, plate numbers, passing card numbers, passing time, toll collection type, etc.) of the toll collection system of road sections, matches the data resources of the mount system, structurally analyzes the data, deeply studies automatic identification, and influences the orientation of the big data analysis result of the platform.

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(3) Relation with the provincial networked toll collection operation management platform of expressways (hereinafter referred to as the operation platform): the platform and the operation platform share data and mutually connect and communicate so as to save the users’ time for the repeated operation among different platforms. The platform provides the data inquiry interface of the image analysis result (such as the vehicle plate, brand, type, and color) as well as the functional interaction of vehicle characteristic analysis and vehicle user imaging.

3.4.4

Functions Realized by the Platform

At present, the platform mainly realizes the following functions: (1) Vehicle user imaging: establish the vehicle user imaging, one file for one vehicle, and form the vehicle credit system under a set of big data. (2) Intelligent operation management: including the intelligent restoration of vehicle traveling track, analysis of vehicle operation data, intelligent monitoring of mount healthy status, etc. (3) Toll-dodging inspection: including the analysis of searching vehicle with image, multi-dimension fast inspection means, analysis of on-road cards, series-parallel analysis of similar plates, analysis of fake plates in service area, analysis of abnormal payment behavior, multiple plates for one vehicle, one plate for multiple vehicles, toll-dodging scout, high-frequent fake plate vehicles, space-frequency analysis, time–frequency analysis, etc. (4) Vehicle traffic safety: including detection of vehicles of dangerous cargoes, detection of trucks traveling on overtaking lanes, detection of buses traveling at night, etc.

4 Conclusion (1) The running results of the platform indicate the loss rate of the passerby cards is greatly decreased. Indicated by No. 23 document Notification of Key Operation Data of Expressways of the Province in 2017, which is issued by the provincial expressway operation management association in 2018, there were 199.5 thousand cash passerby cards which were issued by all entrances but not returned in 2017 and 545 cards lost every day in average. 18631 passerby cards and the toll of 21.47 million Yuan were recovered in 2017. In average, the loss of each passerby card is about 1152 Yuan. The toll loss of the passerby cards of the whole province every year is about 230 million Yuan.

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In 2017, the provincial highway construction Co., Ltd. and the provincial expressway Co., Ltd. cooperated to develop the technical test of the passerby card inspection, extracted 42-million mainline HD mount images of ten provincial main expressway sections in May as the basic data, took 1000 effective passerby card vehicle files as the inspection subject matters, analyzed with the identification technology of vehicle faces and found 51 on-road card vehicles had fake plates, among which 93 plates were involved, and used these fake plates to complete the subsequent traveling tacks of the passerby card vehicles. The ten test road sections are only 10% of all expressways in the province. The test cards were 0.5% of all passerby cards of the test road sections. If the vehicle passing mounts of the province are used as the basic data, it expects the traveling tracks of 50–80% passerby cards can be analyzed, which can greatly decrease the loss of the passerby cards. (2) Before the platform system was constructed, the toll collection inspectors had to manually check massive mount images with the huge-crowd strategy. The efficiency and success rate were both low. After constructed, the platform system greatly reduces the manpower input of toll collection inspection and increases the inspection efficiency and accuracy.

References 1. Jia X (2016) Research on vehicle identification and retrieval technology of deck vehicles 2. Zhu S, Li Y (2018) Face recognition based on SVM and VAR\/LBP. Electron Technol 31(346 (07)):11–14 3. Zhao Y, Gao L, Zhao et al (2015) Model identification technology based on vehicle face characteristics and its application in Public security field. Police Technol 3:81–84 4. Xu JH (2018) Vehicle face recognition algorithm based on edge detection and pattern recognition. Control Eng 5. Qian Z (2011) Research and application of vehicle identification in intelligent transportation system, Sian 6. Yiu C (2016) Research on vehicle face recognition based on convolution neural network

Expressway Vehicle Management System Based on Vehicle Face Recognition Chan Zhang, Lijian Deng, Qicai Du and Weiming Deng

Abstract Facing the problems in the current situation of highway vehicle management, this paper demonstrates the construction of a big data platform based on the vehicle face recognition technology, and uses the technology such as vehicle feature intelligent identification, big data service platform data, platform and external system docking, in order to provide efficient solution for expressway managers, and finally achieves the effect, which pay low cost for the fee of the highway vehicle management, and improves the efficiency and accuracy of the inspection of traffic management.







Keywords Vehicle face recognition Expressway vehicle management Big data

1 Background The number of Chinese motor vehicles in recent years is greatly increasing with the fast development of national economy and the improvement of people’s living standards. The fast extension of expressways and inter-city highways provides great convenience for people’s transportation but also brings many new problems for the expressway traffic management, for example, the toll dodging by on-road cards, fake plates, and cloned vehicles. The problem of violating the traffic regulations on the expressway is also serious. These problems cause a huge loss to the expressway business income as well as a series of hidden dangers of public security order and traffic safety [1]. Under the background that Guangdong province has realized the one toll collection net of province-wide networking of provincial expressways, the mainline toll stations and marking stations which are at the entrances and exits but not the provincial boundaries of the expressways are not used. When the vehicle travels in the province, the driver only needs to get one card and pay once. The payment sum C. Zhang
L. Deng
Q. Du
W. Deng (&) Special Operations Academy of PLA, Guangzhou 510500, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_43

369

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C. Zhang et al.

increases when the vehicle traveling distance on the expressway increases. Thus, driven by interests, the numbers of the toll-dodging vehicles, fake accident vehicles, oil stealing vehicles, smuggled vehicles, intentional traffic violation vehicles, and other suspected vehicles increase, which increases the management difficulty, and these suspected vehicles often have fake plates, no plates, or covered plates. The traditional system based on plate identification cannot solve the problem of identifying these vehicles. The article aims to provide an effective solution for expressway management by establishing the big data platform based on the vehicle face identification technology for all expressways in the province.

2 Current Condition of Toll Collection Facilities of the Expressway Generally, the expressway follows the overall mode that collects the toll and split according to the actual path. It is classified into mobile payment with stop and mobile payment without stop according to the driver’s payment methods which are used as the classification standards. (1) Manual semiautomatic toll collection based on IC card (MTC) The basic flow of the manual semiautomatic toll collection is as follows: manual-type judgment/automatic-type judgment, issue the card by people (or self-service) at the entrance, the camera captures the plate number, verifies the card at the exit, verifies the plate, calculates the toll, manually collects the toll, computer management, video monitoring, and detector check. (2) Electronic toll collection (ETC) without stop based on RFID technology The basic flow of ETC is as follows: the ETC side unit antenna RSU and vehicle-carried unit OBU information communicate to get the information of the vehicle type, entrance, exit, time, etc., and then fast toll collection is realized. The ETC technology which doesn’t use cash for payment increases the pass-through efficiency, reduces the cash management cost, makes the fund recharging and settlement ways be more flexible, and is fast popularized by cooperating with banks. HD mounts and lane HD capturing and plate identification facilities of the main line are additionally arranged at the exit and entrance of each toll station and service area with the unified plan, and the lane-level anti-toll dodging and intercepting function is realized. Although the expressway operation management departments have built a great quantity of video image mount equipment for assisting toll collection and operation management, it is still simple application stage which is based on the plate number retrieval, the entrance and exit mounts, and the mainline mount of the expressway, respectively, belong to the toll collection network and monitoring network but are

Expressway Vehicle Management System …

371

not networked for deep application. With the depreciation of the mount equipment and the variation of the light environment, everyday more than 2-million images in xx province have errors in plate identification and cannot effectively display the vehicle traveling track. The toll-dodging vehicles just dodge the toll by fake plates, no plate, or covered plates and often disappear in the huge number of plates which are wrongly identified, which make the toll collection management personnel and inspectors don’t know how to start.

3 Big Data Platform of Vehicle Face Identification The big data platform of vehicle face identification (hereinafter referred to as the platform) creates the one net for the big data analysis of vehicle face identification through the intelligent analysis and secondary identification of characteristics of all vehicles to the images of the vehicles passing through the expressway image mounts in the province, including the entrance mounts, exit mounts, and mainline mounts. The platform effectively and fast retrieves the brand, color, type, etc., of the vehicle without depending on the plate number and can fast find the suspected vehicle which influences traffic safety or dodges the toll, collect the process and trace information of the suspected vehicle, and consolidate the chain of evidences of toll dodging and influences on traffic safety so as to help the expressway operation, toll collection, and inspection departments pursue the toll dodged by the vehicle. In addition, the platform can also provide evidences of the vehicle and driver who is intentional for traffic violation, fake accidents, drug trafficking, or smuggling to the public security department for effective strikes; thus, the platform can greatly increase the expressway management level [2].

3.1

System Structure

The platform is constructed in two stages, namely the provincial center and road section. The data (images of vehicles passing through the exits, entrances, HD mounts and service area mounts, and pipelining) collected by the front end of the platform are classified, identified and saved, and converted into text data in the stage of road sections, and then sent to the provincial operation center for storage [3] (Fig. 1).

3.2

Logic Structure

The logic structure of the platform system comprises a resource tier, a collection tier, a service tier, and an application tier from bottom to top [4].

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Fig. 1 Big data platform of vehicle face identification

The resource tier mainly comprises all front-end monitoring equipment and mount data collection equipment at the entrances and exits of the toll stations and road sections. It is the perceptual tier of the system and used for capturing road vehicle data. The collection tier mainly comprises the input and storage of front-end data, carries out identification, characteristic extraction and data cleaning and conversion to the passing vehicle information and vehicle image information, and stores the vehicle identification data. The service tier mainly encapsulates the system service and provides data service capabilities to the upper tier, including data retrieval capability, characteristic comparison service, authority management service, data analysis, and computing service. The application tier mainly provides all types of business which conform to expressway demands and encapsulates according to actual demands, including the judgment of on-road cards, analysis of fake plates, analysis of toll-dodging vehicles, etc.

3.3

Storage Structure

The images of the vehicles passing the mounts of the platform are stored in the characteristic identification servers of road section vehicles (if any characteristic identification server of road section vehicles doesn’t have enough space, a separated storage server shall be configured). For saving the investment cost of system construction, the provincial monitoring center doesn’t store the images of the

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vehicles passing the mounts but uses the image URL to quote the images stored in all road sections and calls the image data of all characteristic identification servers of road section vehicles through the network to display the image. Varied by the docking modes of the mount data, the images of vehicles passing the road section mounts in the characteristic identification subsystems of road section vehicles are stored in two ways as following: (1) Directly docking with the mount cameras: after being obtained from the mount cameras, all images are stored in the characteristic identification servers of vehicles, and only the mount image data within 90 days are reserved. The system automatically and circularly deletes the mount image data 90 days before. (2) Getting the image data through the HD mount system: for reducing the construction cost of system storage and ensuring the system can fast check the mount images, the road section identification servers only save the mount data within 30 days. If the system has to access the historic image data 30 days before, the image data stored in the HD mount system is quoted and accessed with the image URL address.

3.4 3.4.1

Core Technology Intelligent Identification Technology of Vehicle Characteristics

The identification technology of vehicle characteristics based on GPU accelerated deep study technology is the core technology of the identification big data platform of vehicle faces. It structures the vehicle image data through vehicle detection, vehicle positioning, type classification, characteristic extraction and identification and comparison, converts image data into the structured data which can be inquired by one key, and cracks the problem that the traditional expressway business only depends on the plate identification but cannot accurately and fast lock the targeted vehicle and personnel activity [5]. The GPU accelerated deep study technology is based on the training of massive vehicle model data and is characterized by fast identification speed, high accuracy, rich identification contents, etc.

3.4.2

Data of Big Data Service Platform

The big data service comprises the core technologies of a distributed file system, a distributed database, a distributed message queue, a distributed search engine, a stream computing framework, etc. The distributed design provides a linear transverse extension capability and provides a reliable, expandable, and fault-tolerant computing system for massive data processing.

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The distributed file system HDFS uses an effective distributed algorithm to distribute data access and storage in a great number of servers and distributes the accesses in all servers of the cluster besides provides the reliable multi-backup storage. It is characterized by self-repair, dynamic capacity expansion, high-throughput capacity, low construction cost, etc. The distributed database HBase is a distributed and column-oriented open-source database. Different from the common relation database, HBase is applicable for non-structured data storage and is characterized by the storage index of massive data, high inquiry and analysis efficiency, optimized storage space, etc. The distributed message column Kafka is a distributed publishing and subscribing message system of high-throughput capacity. It can process producers and consumers’ data models and simplify the system programming model. The Kafka message column provides message persistence with the 0(1) disk data structure and can keep longtime stability of the storage of terabytes of messages and support 100 thousands of messages per second. The distributed search engine Elasticsearch is a Java search engine server based on Lucene. The reverse-order index sorting mode of Elasticsearch provides the search capability of top speed and high throughput as well as the tier-level search and eye-catching display of hit and supports multiple output formats (including ML/XSLT and JSON formats). It is easy to install and configure [6]. The system uses the Storm open-source stream computing framework for the stream computing processing. Storm is a distributed, expandable, and fault-tolerant real-time computing system. Based on the Storm framework, the developer can easily develop the application for continuous stream data processing. Storm is characterized by simple programming model, supporting all programming languages, high fault tolerance, reliable and fast message processing, horizontal expansion based on the thread, progress, and server.

3.4.3

Relation Between the Platform and External System

(1) Relation with the mount system: the platform gets the images of the vehicles passing through the entrances and exits of the toll collections system of road sections and images captured by the mainline HD mount systems and service area mount systems and converts them into the basic data sources of the platform. Thus, the image quantity and quality determine the performance and utilization effect of the platform. (2) Relation with the toll collection system: the platform gets some pipelining fields (pipelining number, plate numbers, passing card numbers, passing time, toll collection type, etc.) of the toll collection system of road sections, matches the data resources of the mount system, structurally analyzes the data, deeply studies automatic identification, and influences the orientation of the big data analysis result of the platform.

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(3) Relation with the provincial networked toll collection operation management platform of expressways (hereinafter referred to as the operation platform): the platform and the operation platform share data and mutually connect and communicate so as to save the users’ time for the repeated operation among different platforms. The platform provides the data inquiry interface of the image analysis result (such as the vehicle plate, brand, type, and color) as well as the functional interaction of vehicle characteristic analysis and vehicle user imaging.

3.4.4

Functions Realized by the Platform

At present, the platform mainly realizes the following functions: (1) Vehicle user imaging: establish the vehicle user imaging, one file for one vehicle, and form the vehicle credit system under a set of big data. (2) Intelligent operation management: including the intelligent restoration of vehicle traveling track, analysis of vehicle operation data, intelligent monitoring of mount healthy status, etc. (3) Toll-dodging inspection: including the analysis of searching vehicle with image, multi-dimension fast inspection means, analysis of on-road cards, series-parallel analysis of similar plates, analysis of fake plates in service area, analysis of abnormal payment behavior, multiple plates for one vehicle, one plate for multiple vehicles, toll-dodging scout, high-frequent fake plate vehicles, space-frequency analysis, time–frequency analysis, etc. (4) Vehicle traffic safety: including detection of vehicles of dangerous cargoes, detection of trucks traveling on overtaking lanes, detection of buses traveling at night, etc.

4 Conclusion (1) The running results of the platform indicate the loss rate of the passerby cards is greatly decreased. Indicated by No. 23 document Notification of Key Operation Data of Expressways of the Province in 2017, which is issued by the provincial expressway operation management association in 2018, there were 199.5 thousand cash passerby cards which were issued by all entrances but not returned in 2017 and 545 cards lost every day in average. 18631 passerby cards and the toll of 21.47 million Yuan were recovered in 2017. In average, the loss of each passerby card is about 1152 Yuan. The toll loss of the passerby cards of the whole province every year is about 230 million Yuan.

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In 2017, the provincial highway construction Co., Ltd. and the provincial expressway Co., Ltd. cooperated to develop the technical test of the passerby card inspection, extracted 42-million mainline HD mount images of ten provincial main expressway sections in May as the basic data, took 1000 effective passerby card vehicle files as the inspection subject matters, analyzed with the identification technology of vehicle faces and found 51 on-road card vehicles had fake plates, among which 93 plates were involved, and used these fake plates to complete the subsequent traveling tacks of the passerby card vehicles. The ten test road sections are only 10% of all expressways in the province. The test cards were 0.5% of all passerby cards of the test road sections. If the vehicle passing mounts of the province are used as the basic data, it expects the traveling tracks of 50–80% passerby cards can be analyzed, which can greatly decrease the loss of the passerby cards. (2) Before the platform system was constructed, the toll collection inspectors had to manually check massive mount images with the huge-crowd strategy. The efficiency and success rate were both low. After constructed, the platform system greatly reduces the manpower input of toll collection inspection and increases the inspection efficiency and accuracy.

References 1. Jia X (2016) Research on vehicle identification and retrieval technology of deck vehicles 2. Zhu S, Li Y (2018) Face recognition based on SVM and VAR\/LBP. Electron Technol 31(346 (07)):11–14 3. Zhao Y, Gao L, Zhao et al (2015) Model identification technology based on vehicle face characteristics and its application in Public security field. Police Technol 3:81–84 4. Xu JH (2018) Vehicle face recognition algorithm based on edge detection and pattern recognition. Control Eng 5. Qian Z (2011) Research and application of vehicle identification in intelligent transportation system, Sian 6. Yiu C (2016) Research on vehicle face recognition based on convolution neural network

Study on Application of Transfer Path on Micro-vibration Test for Satellite Gongbo Ma, Yao Wu, Dong Wang, Zhiyong Yue, Jiang Yang and Rui Wang

Abstract During the orbit process of spacecraft, various disturbance sources inside would cause micro-vibration response, which reduces its observation resolution and affects the captured quality; so, it is necessary to conduct micro-vibration tests on the ground to evaluate spacecraft’ orbit performance. However, in the ground micro-vibration test, the noise generated by the internal disturbance of the spacecraft will produce a small response to structure due to the air effect that makes micro-vibration environment of high-resolution satellite on the ground is inconsistent with that in orbit. In order to research the influence of noise environment in the ground test, this paper analyzed CMG noise and its characteristics and used a small motor instead of CMG and designs satellite simulator on which micro-vibration test was designed based on transfer path analysis. Finally, the contribution of disturbance source was analyzed to evaluate the influence of CMG noise on micro-vibration test on the ground.




Keywords Satellite Micro-vibration test analysis Contribution





Disturbance noise
Transfer path

1 Introduction Noise caused by disturbance such as CMG would appear in micro-vibration test because of air effect on the ground. For satellites with high resolution, disturbing noise would affect imaging quality, and micro-vibration test cannot identify disturbance’s influence effectively and even lose its own meaning. For quantitative analysis method on the influence from disturbing noise to test precision, noise contribution analysis must be conducted. At this point, transfer path analysis was applied which processes the FRF and responses measured with certain mathematical method to separate the energy flow transferring from source G. Ma (&)
Y. Wu
D. Wang
Z. Yue
J. Yang
R. Wang Beijing Institute of Spacecraft Environment Engineering, Beijing 100094, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_45

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(force/noise) to target (throughout air or structure) to assess the influence of disturbing noise as Fig. 1. Direct method can’t be achieved in actual satellite test for that acoustic simulator which work well in low-frequency stage can’t be taken into the disturbing position. While transfer path analysis can get the contribution of noise by measuring and processing the FRFs and responses. Van Der Linden et al. [1, 2] carried out structural noise transfer characteristics analysis and measured the mechano-acoustic frequency response function based on the reciprocity principle in the analysis process. In 2003, Krishna R D et al., proposed a subsystem NVH target-setting method based on TPA technology. Gregor et al. [3] proposed a method based on the transposition of transfer path matrix when analyzing engineering examples of noise contribution of vehicle body parts. In 2008, De Sitter et al. [4] proposed a method for analyzing the transmission path in the operating condition, which used the operating condition signal to construct the frequency response function, greatly improving the efficiency compared with CTPA. Tongji University studied TPA method earlier. From 2001 to 2002, Zhang et al. [5, 6] applied TPA method to the practice of reducing vehicle interior noise. Above all, TPA application domestically and abroad has not exploited the advantage of TPA in guiding disturbance contribution analysis in spacecraft, especially for high-resolution satellite. How to use transfer path analysis to recognize the response on camera by disturbing noise made of disturbance as CMG (control momentum gyroscope) desiderates exploration and research imminently.

Fig. 1 Schematic diagram of satellite disturbance source contribution analysis test

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In this paper, a valid assessment for the contribution of disturbing noise to micro-vibration test is a fundamental purpose. Firstly, satellite model was produced; then, imitate disturbance was chosen and its disturbing force and noise were extracted. Afterward, FRFs and micro-vibration responses were measured based on TPA. Finally, the data measured was processed by TPA to calculate the contribution of disturbing noise and vibration among the whole response.

2 Disturbance Property Research and Simulation Analysis This paper conducted experiment to research the contribution of disturbing noise. Vibration and noise have been measured by force platform and sound pressure sensor against the CMG.

2.1

Choice of Simulant Disturbance

The property of disturbing force and noise of 7000 rpm CMG had been measured as Fig. 2. Figure 2a can see that the disturbing force can rise to max around working frequency. Figure 2b can see that the disturbing noise can rise to max around working frequency.

(a)

(b)

Fig. 2 a CMG disturbing force property, b CMG disturbing noise property

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Considering small installed space and bad SNR for low frequency, 24 V DC Motor has been chosen for its small size, stable working frequency, and adjustable speed-gear (5400–9000 rpm).

2.2

Simulant Effect Analysis

Install the motor directly on flange of force-measure platform with 502 glue as Fig. 3, and then turn on the motor and measure its disturbing force and noise spectrum. The result is Fig. 4: Force can rise to max at the working frequency and its multiple and the same to noise which is bigger than background noise. In summary, stimulant effect is better for its similar appearance to CMG.

(a)

(b)

Fig. 3 a Test for motor disturbing force, b test for motor disturbing noise

(a)

(b)

Fig. 4 a Spectrum of motor disturbing force, b spectrum of motor disturbing noise

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3 Experiment Design and Contribution Analysis Based on TPA In this section, experiments were designed under free boundary condition where the simulated disturbance source was installed at the installation module and the target and reference points were distributed. The procession of test is shown as Fig. 5.

3.1

Measuring-Point Arrangement and Model Design

Disturbance source excitation consists of three directions of force excitation and acoustic excitation in all four parts. The number of reference points should be no less than 4 for full rank of structure frequency matrix. Selection of target and reference points is shown in Table 1.

3.2

Equipment Installation

Testing condition is shown in Fig. 6, and suspension frequency in all directions in Table 2, in which free boundary condition is satisfied that all suspension frequencies are less than 8 Hz. Then, use hammer to strike all points, respectively, and get FRFs and response (motor working) for TPA.

Fig. 5 Procedure of disturbance contribution analysis on transfer path analysis

Table 1 Reference point selection Target point Excitation point Reference points

A13Z A1X, A1Y, A1Z A2Y, A3Y, A4X, A5Y, A6Y, A7X, A8Y, A9X, A10Y, A11Z, A12Z

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Fig. 6 Testing condition

Table 2 Suspension frequency

Direction Suspension frequency (Hz)

X 1.5

Y 1.7

Z 2.4

RX 0.8

RY 0.6

RZ 2.1

4 Contribution Analysis In this section, based on the FRF and response measured, the local load (sound/ vibration) of the simulated disturbance source on the test piece is identified by TPA method and the contribution is calculated, which provides a basis for the analysis of noise and disturbance contribution rate on the satellite in the future.

4.1

Load Identification

By the rigid connection between the active side and the affected party in the satellite test, in this paper, the generalized inverse of the frequency response function matrix from the excitation load to the response of the reference point of the passive end structure is multiplied by the response of the reference point of the passive end structure under the operating condition to obtain the excitation load force. The sound transfer function of the main direction to the excitation point is obtained by tapping each target point and reference point by overforce hammer method. Structure/acoustic frequency response matrix of all transmissions composed of test pieces:

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2

H13Z;1X H2Y;1X 6 .. .. 6 . H¼6 . 4 H13Z;1Z H2Y;1Z H13Z;S1 H2Y;S1

3


H12Z;1X .. .. 7 . . 7 7


H12Z;1Z 5


H12Z;S1

ð1Þ

In which HiZ;jX ¼ AFjXiZ ; HiZ;S1 ¼ PFS1iZ . Fiz is the excitation force in the Z direction of point i. The reference point/target point response matrix X and the load matrix F are, respectively: X ¼ ½ A2Y






A13Z 

X ¼ ½ Fx

Fy

Fz

Q T

F ¼ HþX

ð2Þ ð3Þ

Finally, the spectrum of the disturbing force/noise in all directions is recognized as Fig. 7a, and its comparison with measured data is shown in Fig. 7b which shows that the identifying disturbing force is basically consistent with the measured value.

4.2

Contribution Calculation

Adjust the speed of the disturbance source to working at 7400 rpm, then measure the response of each reference point and target point at different speeds. Analyze the contribution rate of the disturbance source by transfer path method. The analysis result is shown in Fig. 8. It can be seen that there is small distinction between the total contribution in the analysis result and the measured value in terms of value and phase.

(a)

(b)

Fig. 7 a Load identification result, b comparison of identification and measurement

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Fig. 8 Disturbance contribution analysis in 7400 rpm

The disturbance contribution rate is defined as follows: k¼

AðFi Þ
cos uðAðFi ÞÞ  uðAðFÞÞ AðFÞ

ð4Þ

In which A(F) and uðAðFÞÞ respectively expresses the amplitude and phase of total contribution, while A(Fi) and uðAðFi ÞÞ indicate respectively the amplitude and phase of single force’s contribution. There may be a gap between the total contribution obtained by the transfer path analysis and the measured response, which may lead to unreliable analysis results. Therefore, the total response error is defined to evaluate the accuracy of analysis results: f¼

AðFÞ
cosðuðAðFÞÞ  uðAreal ÞÞ Areal

ð5Þ

The contribution analysis is carried out for the response at the operating frequency of 124 Hz. The contribution rate of each disturbing force and noise and the total response error are shown in Table 3.

Table 3 Analysis for contribution by any load and deviation Load

Fx (%)

Fy (%)

Fz (%)

Q (%)

Calculation deviation (%)

Contribution

2.6

−42.6

−43.4

8

4

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5 Conclusions In this paper, the noise characteristics of CMG with different states are measured and its regularity is analyzed to solve the problem of the influence of CMG noise on the structural response in micro-vibration test, and the small scrambling source is used to simulate CMG; the micro-vibration test for the basic transfer path method is designed, and the contribution of the noise to the total response is calculated by analyzing the test data. The main conclusions of this paper are as follows: 1. Analog disturbance source’s volume is small; the frequency spectrum law of disturbing force and noise sound pressure is similar than that of actual CMG. 2. The acceleration response reaches the peak at the main frequency of the disturbance source, and the total response error is much smaller than the contribution rate of the sound and disturbance vibration. 3. The contribution of the noise source to the response of the farthest point of the simulator is less than the contribution of the disturbing force.

References 1. Van Der Linden PJG, Fun JK (1993) Using mechanical acoustic eciprocity for diagnosis of structure borne sound in vehicles. SAE Technical Paper Series, Michigan, USA, Paper Number 931340 2. Van Der Linden PJG, Varet Ph (1996) Experimental determination of low frequency noise contribution of interior vehicle body panels in normal operation. SAE Technical Paper Series, Michigan, USA, Paper Number: 960194 3. Gregor K (2003) Panel noise contribution analysis: an experimental method for determining the noise contributions of panels to an interior noise. SAE Technical Paper Series, Michigan, USA, Paper Number 2003*01*1410 4. De Sitter G, Devriendt C, Gidllaume P et al (2010) Operational transfer path analysis. Mech Syst Signal Process 24:416–431 5. Zhang L, Zhou W, Yu ZP (2001) Research on control of car interior noise due to engine vibration. J Vibr Measur Diagnosis 21(1):59–64 6. Zhang L, Jing X, Yu Z (2002) Research on the reduction of car interior noise. Autom Eng 24 (1):15–19

Hierarchical Processing Model Based on Multi-modality Interaction Design Aiguo Lu, Bo Dong and Feiran Hu

Abstract The information warfare requires diverse operations and a lot of information, the traditional human factors engineering design methods are prone to problems of high load of human–computer interaction, and it also lacks of quantitative capability. This paper focuses on five modalities of voice, eye control, touch, brain control, and gestures, and according to the man–machine–environment cognitive decision model and the hierarchical processing model for each modality interaction in different applicable scenarios to build the multi-modality interaction layered processing model to enhance the naturalness and friendliness of command interaction. Keywords Shipborne command and control system computer interaction design


Multi-modality
Human–

1 Introduction Information system-based system combat capability is an important goal of naval construction. Its function is to achieve coordination between “commander (man)combat command system (machine)-combat situation (environment)” through a natural and efficient command and control environment. It assists the commander to complete the transition from information superiority to decision-making advantage. Therefore, human factors engineering design technology, which comprehensively considers the influence of various factors of “human–machine–environment” and can effectively improve the ability of commanders to interact with information systems, plays an important role in guiding the construction of combat information

A. Lu (&)
B. Dong
F. Hu Wuhan Digital Engineering Institute, Wuhan 430205, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_46

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systems. Under the guidance of human factors engineering, the future combat information system should make the relationship between system software more friendly, more adaptable, and more beneficial.

2 Man–Machine–Environment Cognitive Decision Model In the operational command process, the ability of human–computer interaction is related to operational intent, interaction mode, and operational environment. Therefore, in the design of human factors engineering, it is necessary to comprehensively consider the operational tasks, commanders’ habits, situational intelligence and other influencing factors and establish an intelligent model that can comprehensively recognize and decide on various human factors.

2.1

Human–Computer Interaction Environment

The operational command interaction environment is mainly composed of commanders, multi-channel interaction devices, interaction modes, interaction information, and interaction scenarios [1]. The commander controls and operates the weapon equipment through interactive information to release the combat command; the interaction information is generated by interaction, and the generation of the interaction information is also affected by the interaction scenario as shown in Fig. 1. The working process of the commander in the command environment is the process of uninterrupted interaction with the accusation equipment through different interaction modes; that is, the command environment receives and manages information from all directions of the battlefield, through the comprehensive visualization technology in the command and control system [2]. The commander displays the information needed for the current battlefield situation and decision making, so that the commander can quickly perceive the current situation of the battlefield, thereby improving the operational efficiency.

2.2

Human–Computer Interaction Model

The command and control system acts as a bridge between the accusation equipment and the commander. In the command and control system, different functions correspond to different interaction tasks, and the interaction tasks need to be analyzed and designed according to the types of data obtained by different interaction tasks and interaction channels [3]. Each interaction in the command space relies on a conceptual model of each channel. The model can convert the natural information generated by any action of the interactive mode into a certain format of metadata,

Hierarchical Processing Model Based on …

Base layer

Commander

397

mutual restraint influences

feedback using

Interactive information

Interactive mode

Interactive information using

Interactive scene mutual restraint

control

Equipment

Domain layer Instance layer

commander

equipments

elements

Fig. 1 Combat command interaction environment

and then convert the metadata into a machine information format through mapping, and the machine reads the information and converts it into a corresponding execution command (Fig. 2). The command-environment-interaction model is the interaction of the personnel, equipment, interaction environment, interaction mode, interaction information, and other interactive elements in the operational command space to form a comprehensive description of the entire command space interaction model [4].

3 Hierarchical Processing Model for Each Modality Interaction in Different Applicable Scenarios In the research of this project, the multi-channel integration of EEG, eye movement, voice and gestures in addition to the traditional mouse and keyboard control is used to construct the command and control system interaction task. The gesture channel includes two different channels, the touch gesture and leap motion gesture. The touch gesture corresponds to the touch modality and the leap motion gesture corresponds to the leap modality in Fig. 3.

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Fig. 2 Human–computer interaction model

The performance of the above channels and the environmental factors is shown in Tables 1 and 2. According to different channel characteristics, selecting the appropriate interaction mechanism for different interaction operations is the key to improving the naturalness and efficiency of multi-channel interaction.

Hierarchical Processing Model Based on …

Command and control system

399

EEG modality

Different EEG signals provide corresponding interac ve tasks

Eye movement modality

Different ocular signals provide corresponding interac ve tasks Alarm informa on input

Voice modality

Vocabulary and command input through sound Different gestures provide corresponding interac ve task parameters

Touch modality

Wri ng gestures provide corresponding interac ve tasks

Leap modality

Dynamic gestures provide corresponding interac ve tasks

Fig. 3 Interactive content and role of different channels

Table 1 Interactive channel performance comparison Interactive modality

Mouse modality

Voice modality

Touch modality

Leap modality

EEG modality

Eye movement modality

Question and answer interaction based on menu icons Information output efficiency Information input efficiency Support for fuzzy and continuous natural input Number of cognitive subjects Operational accuracy requirements

✓

✓

✓

✓

✓

✓

Low

Low

Low

Low

High

High

Low

High

High

High

High

High



✓

✓

✓





Single

Single

Multiple

Single

Single

Single

High

Low

Low

Low

High

High

Table 2 Each modality is affected by environmental factors Interactive modality

Mouse modality

Voice modality

Touch modality

Leap modality

EEG modality

Eye movement modality

Complex light environment Complex acoustic environment Vibrating environment Complex temperature and humidity environment

✓

✓





✓

✓

✓



✓

✓

✓



✓ 

✓ ✓

 

✓ ✓

✓ 

✓ ✓

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Table 3 Analysis of the advantages and disadvantages of touch modality Advantages

Disadvantages

Advantages in menu activation tasks, especially when there are more menus and levels, the advantages are more obvious It has advantages in text entry, and the operation mode is more in line with the natural interaction mode Non-contact control This control method is robust in complex acoustic environments

The complex light environment and the swaying condition have great influence; especially for the vocal sensitivity, it is easy to cause recognition errors and misoperations (Note: this deficiency can be overcome by combining with other interactions)

3.1

Touch Channel and Its Applicable Scenarios

The touch gesture channel is to acquire the touch point state information of the user on the screen, including the number of points and the coordinates of the point, and then combines the meanings of the predefined information according to the change of the information, thereby forming a meaningful operation. Changes in the state of the touch point are caused by atomic interactions, and each touch point on the screen is equal. The advantages and disadvantages of the touch channel are shown in Table 3.

3.2

Gesture Channel and Its Applicable Situation

The gesture recognition-based input mechanism refers to the gesture recognition device generating a specific operation command after recognizing a specific gesture. This mechanism is suitable for basic operations of clicks and advanced operations. The advantages and disadvantages of gesture control are shown in Table 4.

Table 4 Analysis of the advantages and disadvantages of gesture modality Advantages

Disadvantages

Advantages in menu activation tasks, especially when there are more menus and levels, the advantages are more obvious Non-contact control This control method is robust in complex acoustic environments

In complex light environments and sway conditions, it is easy to cause recognition errors and misoperations (Note: this deficiency can be overcome by combining with other interactions)

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401

Table 5 Analysis of the advantages and disadvantages of voice modality Advantages

Disadvantages

Advantages in menu activation tasks, especially when there are more menus and levels, the advantages are more obvious It has advantages in text entry, and the operation mode is more in line with the natural interaction mode This control mode is robust in complex light environments and rocking conditions Non-contact control

The control effect is greatly affected by the acoustic environment of the cabin; especially for vocal sensitivity, it is easy to cause recognition errors and misoperations (Note: this deficiency can be overcome by combining with other interactions)

3.3

Voice Channel and Its Applicable Scenarios

Using highly reliable military language recognition technology, the command and control system can automatically identify and understand the commander’s password and quickly execute the corresponding commands and operations while the commander uses the traditional password to issue operational commands. The applicable scenario is that the user’s hands are no longer limited to operating the computer; the text input and the command can be issued efficiently and accurately, and the advantages and disadvantages thereof are as shown in Table 5.

3.4

Eye Movement Channel and Its Applicable Situation

In human–computer interaction technology based on EO signal control, it is the key to effectively extract and utilize the eyeball to obtain information. On the basis of subjective consciousness to control the eyeball to make corresponding actions: blinking, glance, gaze, etc., the EOG signal is collected by the sensor, and the signal is analyzed and processed to obtain useful information, and finally the analysis and processing result is encoded according to a certain rule, thereby achieving control of external auxiliary equipment. The advantages and disadvantages of eye movement control are as shown (Table 6).

3.5

EEG Channel and Its Applicable Scenarios

Brain–computer interaction can use the brain activity to scroll through menus, select icons, enable applications, and even enter text. This high-performance, noninvasive and intuitive brain–computer interaction can solve the problem that the operational commander’s information load is huge, the task is heavy and urgent,

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Table 6 Analysis of the advantages and disadvantages of eye movement modality Advantages

Disadvantages

It has the advantage of target selection and activation in the visual search task, and can achieve the “what you see is what you get” natural interaction mode, especially when using the gaze mode, both performance and subjective satisfaction are higher During the use, the user does not need to perform limb operation and does not need special signal acquisition training This control method is robust in noisy environments The eye movement signal has obvious time-domain characteristics, the signal acquisition experiment is simple and easy to operate, the acquisition equipment is popular, and the price is cheap

Limited by the maturity of the current eye movement control technology itself, the eye load is currently large when performing the target drag task, and is not suitable for long-term operation Control effects may be affected by light conditions and ship swing conditions The above two points are based on the current eye movement control technology. With the advancement of technology, the above deficiencies can be solved

Table 7 Analysis of the advantages and disadvantages of EEG modality Advantages

Disadvantages

Significant advantage in fast order release Non-contact control This control mode is robust in complex light environments, rocking conditions and complex acoustic environments

Need pre-training (Note: This deficiency can be overcome by combining with other interaction methods)

and the human–computer interaction is limited, and the control obstacles are urgently needed. The advantages and disadvantages of EEG control are shown in Table 7.

4 Multi-modality Interaction Layered Processing Model In order to achieve multi-channel interaction, it is first necessary to model the multi-channel interaction process. Based on the above-mentioned command environment interaction model, this paper adopts the multi-channel interaction layered processing model and divides the information transmitted in the application according to the processing needs, and tries to ensure that the path of information transmission is the shortest and effective as the standard, and is divided into different levels.

Hierarchical Processing Model Based on … Database

Applica on

Interac ve control

Interac ve informa on

Interac ve database (human factors data, environment and device data, etc.)

Applica on database

Output by input computer according to user intent Integrate the data of all par es to calculate the control amount of output informa on of each channel Enter informa on

Output informa on

Image, audio, touch, eye, brain, environment...

Vision, listening, touch, environment...

WIPM interface

user-interface

Interac ve modality

Physical world

403

Touch informaon

Gesture informaon

Voice informaon

Touch modality

Leap modality

Voice modality

Eye movement informaon Eye movement modality

Operator

EEG informaon

Environment informa on

EEG modality

Context aware device

Envirnmental factor

Fig. 4 Multi-modality interaction layered processing model

The system contains multi layers of the interaction environment, commander, multi-channel interaction device, interaction mode, interaction information, and interaction scenario Fig. 4.

5 Conclusion and Perspective This paper focuses on five modalities of voice, eye control, touch, brain control and gestures, and studies multi-modality human–computer interaction design technology for combat “human–machine–environment” deep interaction requirements, and realizes interactive modes under various modalities. Effectively integrate and adopt an intelligent method to improve the autonomy of interaction design and has the ability to adapt to changes in the operational environment.

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References 1. Leite H, De SC, Costa T et al (2018) Analysis of user interaction with a brain-computer interface based on steady-state visually evoked potentials: case study of a game. Comput Intell Neurosci 2018(2):1–10 2. Chen J, Cao WH, Zhao H (2008) Application research of TAO in shipborne command and control system. Comput Eng 34(11):237–238 3. Jia P, Xiao-Gang XU, Zheng WT et al (2013) Battlefield visualization research on shipborne command and control system. J Syst Simul 25(10):2355–2358 4. Hsu LY, Loew MH (2001) Fully automatic 3d feature-based registration of multi-modality medical images. Image Vis Comput 19(1):75–85

Application of Pipeline Ventilation Efficiency Test in Sanitary Ventilation Engineering Huijun Zhang and Shulin Zhou

Abstract The detection of ductwork ventilation efficiency is a basic technical method and method for the effectiveness evaluation of occupational health protection engineering, and it is also a necessary process for the diagnosis of existing problems in the ventilation system. According to the occupational health evaluation of the parameters, such as ventilation efficiency assessment requirements, this paper introduces the ventilation pipe of the measurement of wind speed and wind pressure and illustrates the concept and method of the new air volume and air changes; the use of the commonly used measuring instrument was introduced in detail; the field measurement method and the calculation process are presented to avoid to produce error methods, requirements, and matters needing attention; That how to select measuring method, measuring instrument and its suitability according to work condition are expounded, which has guiding reference for pipe ventilation efficiecy testing and evaluation. Keywords Velocity


Pressure
Measurement

1 Overview The ventilation of the protection facility in the sanitary engineering aims to continuously supply clean fresh air into the workshop for diluting the harmful substance concentration in the air of the workshop as well as exhaust the polluted air [1]. It is the close relevant technical measure for controlling the industrial harmful substances and dust and poison prevention work [2]. It can effectively prevent fire and explosion, improve the air quality and comfort of the work environment, and protect the workers’ health. Thus, measuring the ventilation system is necessary for assessing occupational safety and sanitary protection facility.

H. Zhang (&)
S. Zhou China Academy of Safety Science and Technology, Beijing 100029, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_47

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Industrial ventilation can be classified into local ventilation and overall ventilation according to the service range [3], wherein the local ventilation is mainly used for exhausting harmful substances, and the overall ventilation is mainly used for the overall air exchange of the environment. The controlled hood face air velocity is the assessment index of the local ventilation facility, while the fresh air volume or air exchange times is the assessment index of the overall ventilation facility. As ruled by GBZ1-2010 Hygienic Standards for the Design of Industrial Enterprises, the fresh air volume per capita of the workshop using air-conditioning shall be  30 m3/h and the fresh air volume per capita of the cleaning room shall be  40 m3/h [4]. Necessary measurement must be carried out to the ventilation facility so as to diagnose the problems in the work environment and then find out the effective solution.

2 Air Exchange Times and Fresh Air Volume The measured values of the fresh air volume and air exchange times are sourced from the ventilation volume of the airports. The fresh air volume is as follows: (fresh air volume = ventilation volume/beneficiary people number). The air exchange times is as follows: (air exchange times = ventilation volume/ effective indoor volume). The ventilation volume of the airports depends on the product of the area of the ventilation ports (mechanical ventilation inlets, fresh air inlets, and natural ventilation windows) and the mean air velocity. The air velocity is measured as follows: equally divide the ventilation inlets into a plurality of parts, use the anemometer to respectively measure the air velocity of each part, and then solve the mean air velocity of the ventilation inlets. Points shall be distributed at the external air inlets of the ventilation system for measuring the fresh air volume. The points can be distributed at the fresh air outlets if the points cannot be distributed at the external air inlets. Points can be distributed at the main air outlet and return air outlet if the points cannot be distributed at the external air inlets and there is no independent indoor fresh air outlet.

3 Classification of Ventilation Measurement The measurement parameters of ventilation are from air velocity measurement and air pressure measurement, wherein the former is generally carried out at the airports, such as air inlets or air outlets, and the latter is generally carried out in the ventilation pipeline.

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Measurement of Air Velocity

The impeller anemometer or the hot-ball-shaped anemometer can be used for directly measuring the air velocity, wherein the former comprises of a wing-shaped impeller of which the measurement range is from 0.5 to 10 m/s and a cup-shaped impeller of which the measurement range is from 1 to 40 m/s. The blade rotating shaft of the impeller anemometer in actual measurement shall be consistent with the air direction. It shall face the upwind direction and the measurement personnel’s body or any other object shall not hinder the current flowing. It shall ensure the action synchronization of the instrument gate and stopwatch. The air velocity result needs to be calculated out. The measurement value of the instrument has the accumulation effect; thus, the instrument is more applicable for the method of continuous measurement of slowly and evenly moving on a special route in the effective area. The hot-ball-shaped anemometer can directly read out the air velocity value, but its result shall be corrected according to its calibration curve. The measurement range of the hot-ball-shaped anemometer can be 0.05–30 m/s. The cap-type air volume hood can directly measure the air volumes passing all airports (air diffuser, shutter, etc.). Its principle is that a closed woven hood passage is made from light materials, the hood face of the woven hood is provided with the matrix comprising of a plurality of pressure sensor, and then the wind velocities at all points can be measured. The error of scattered measurement and the randomness of manual measurement are avoided. When used, the air volume hood is arranged on the airport, and then the digital display can directly read out the air inlet volume or air outlet volume.

3.2

Measurement of Air Pressure

The air pressure measurement in the ventilation system duct comprises of the static pressure, dynamic pressure, and total pressure of the air. The measurement at this time can only be carried out in the pipeline. The airflow rate is directly proportional to the square root of the dynamic pressure of the position. The expression is formula (1). The total pressure is the algebraic sum of the static pressure and dynamic pressure; thus, it only needs to measure the total pressure and static pressure during actual measurement, and the dynamic pressure can be calculated out or directly measured through the connection of the test pipe.

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4 Pressure Test 4.1

Test Hole and Test Points

For improving accuracy, it shall prefer to choose the test holes of test section on the direct pipe section with stable current. When the test site cannot fully meet the requirement, the test section in principle can be set on the position of which the distance is not shorter than 3 times of the pipeline diameter in the upstream direction (flowing direction of relative current) of the elbow-, tee-, or other irregular-shape component. When the test section is at the back of the components above, the distance of the position to these components shall be not shorter than 6 times of the pipeline diameter. The test section shall not be used as the test holes if the dynamic pressure of any test point is zero or negative during measurement because zero or negative dynamic pressure indicates the current is unstable and there is the vortex. Also, if the current direction deviates from the air pipe central line for more than 15°, the section shall not be used as the test hole, either. (detection method: face the end of the pitot pipe to the current direction, and slowly rotate the pitot pipe until the dynamic pressure is maximum; the included angle between the pitot pipe and the vertical line of the outer wall of the air pipe is the deviation angle between the current direction and air pipe central line). It shall consider the convenience and safety for measurement when selecting the test holes. The frictional resistance of the pipeline makes the air flowing velocities at all points of any section different, even in a stable straight pipeline. The guiding principle for setting test points is as follows: divide a plurality of spaces of same area on a section, and then measure at the central point of the physical size. Thus, the test hole shall be selected according to the pipeline shape.

4.1.1

Circular Duct

Set two mutually vertical test holes on the same section, and divide the pipeline section into a number of concentric rings of same area. The number is determined according to Table 1. Figure 1 shows the layout of the test points of the duct which is divided into two concentric rings, and the test points of the other concentric rings can be arranged in the same way. For the circular duct, the distances of all test points on the concentric rings to the inner wall of the duct are shown in Table 2 [2].

Table 1 Number of circular air ducts Duct diameter D (mm)

1150

Dividing number (n)

2

3

4

5

6

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Fig. 1 Arrangement of circular wind duct observation points

Table 2 Distance coefficient between the circular duct measuring point and the wall (take the pipe diameter as the radix) The serial number of measuring points

With heart ring number 2 3

1 2 3 4 5 6 7 8 9 10 11 12

0.933 0.750 0.250 0.067

4.1.2

0.956 0.853 0.704 0.296 0.147 0.044

4

5

6

0.968 0.895 0.806 0.680 0.320 0.194 0.105 0.032

0.975 0.92 0.85 0.77 0.66 0.34 0.226 0.147 0.081 0.025

0.98 0.93 0.88 0.82 0.75 0.65 0.36 0.25 0.177 0.118 0.067 0.021

Rectangular Duct

The section of the rectangular duct can be divided into a plurality of small rectangles of same area, the test points are distributed at the center of each small rectangle, and the length of each edge of the small rectangle is about 200 mm, as shown in Fig. 2. The number and positions of the test holes are set according to the actual condition.

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Fig. 2 Layout of rectangular air duct measurement points

4.2 4.2.1

Test Instruments U-Shaped Pressure Gauge

The U-shaped pressure gauge is not applicable for measuring micropressure and generally can measure the pressure from 200 to 6000 Pa. Its minimum division value shall not be higher than 10 Pa. When used, the U-shaped pressure gauge must be vertically hung on the wall or support; then fill working liquid into the U-shaped glass pipe according to the tested pressure. The best condition is that the working liquid reaches 1/2 of the ruler scale. It shall follow the three points as follows in actual utilization: (1) Before measurement, it must confirm the maximum range of the pressure gauge is higher than the tested pressure in case that the working liquid overflows from the glass pipe. (2) It must keep the inner wall of the glass pipe is clean and the working liquid is pure. When not used, the nozzle shall be covered by gauze or other object in case that the test precision is influenced. (3) Before test, adjust the instrument to be vertical, check is there any air bubble in the liquid column, force the residual air out, and adjust the liquid level to zero. Then, connect the pressure test pipe with the pressure gauge with a rubber pipe according to the test content.

4.2.2

Inclined-Type Micropressure Gauge

The inclined-type micropressure gauge can measure the range from 0 to 500 (50, 1000, 1500 and 2000) Pa by adjusting the inclined angle with the precision of 1.0 level. Its minimum division value shall be not higher than 2 Pa. It shall note the following: (1) Horizontally adjust the instrument; check is there any air bubble in the liquid column; repeatedly squeeze the rubber pipe to force the air bubble out and

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make the liquid level be a little lower than the nozzle; and adjust the liquid level to zero. (2) Check if the micropressure gauge leaks; blow (or suck) the inlet of the positive pressure end (or negative pressure end) of the micropressure gauge; and fast close the inlet. If the liquid column position of the micropressure gauge does not change, it means it does not leak.

4.3 4.3.1

Determination Preparation Before Determination

At first, check if the Pitot pipe leaks according to the following method: connect the outlet of the total pressure pipe with the positive pressure end of the inclined type micro pressure gauge with the rubber pipe, and connect the outlet of the static pressure pipe with the negative pressure end of the inclined type micro pressure gauge with the rubber pipe; blow from the test hole of the total pressure pipe and then fast block the test hole, if the liquid column position of the inclined type micro pressure gauge doesn’t change, it means the total pressure pip doesn’t leak; seal the static pressure test hole with the rubber pipe or adhesive tape; and then open the full-pressure test hole, the liquid column of the inclined type micro pressure gauge will drops to a position, and it means the static pressure pipe doesn’t leak if the liquid doesn’t drop any more. In addition, the test point data (insertion depth in the pipeline) calculated out in Sect. 4.1.1 or Sect. 4.1.2 are respectively marked on the wall of the pitot pipe adhered with white adhesive tape.

4.3.2

Pipeline Connection

(1) When the U-shaped pressure gauge is used for measuring the total pressure or static pressure, one end of the pressure gauge is connected with the pressure nozzle, and the other end directly communicates with the atmosphere. For measuring the dynamic pressure, one end is connected with the total pressure nozzle and the other end is connected with the static pressure nozzle. Read the height difference of the levels at both ends of the pressure gauge. Figure 3 shows the methods for connection of the pitot pipe and U-shaped pressure gauge when measuring the total pressure, static pressure and dynamic pressure. (2) When the inclined-type micropressure gauge is used for measurement, poke the valve handle of the micropressure gauge to the position of pressure test; if the tested pressure is higher than the atmospheric pressure, connect the measured

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Fig. 3 Connection between pitot pipe and U-shaped pressure gauge

pressure nozzle to the “+” pressure connector of the valve; if the measured pressure is lower than the atmospheric pressure, at first the middle connector of the valve and the connector at the upper end of the inclined measurement pipe shall be communicated with the rubber pipe, and then connect the measured nozzle to the “−”pressure connector of the valve; and for measuring pressure difference, connect the measured high-pressure pipe with the “+” pressure connector of the valve, connect the low-pressure pipe of the measured pressure with the “−” pressure connector of the valve, and the middle connector of the valve and the connector at the upper end of the inclined measurement pipe are communicated with the rubber pipe. When reading, the reading on the inclined measurement pipe shall be multiplied by the constant factor of the corresponding arc-shaped support. Figure 4 shows the connection of the pitot pipe and the inclined-type micropressure gauge [5].

Fig. 4 Connection between pitot pipe and tilting micromanometer

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Test

The S-shaped pitot pipe shall be inserted into the test hole under the status that the opening plane is vertical to the measurement section so as to reduce the impact on the pressure gauge during insertion. The reading of the micropressure gauge at this time shall be about zero. Before inserting the standard pitot pipe into the pipeline, the passage of the pitot pipe and the micropressure gauge shall be clenched by hand to cut off their connection and prevent the alcohol in the micropressure gauge from being sucked into the connection pipe. It shall affirm the total pressure opening of the pitot pipe and the flow direction of the air in the pipeline before insertion and ensure the total pressure opening faces the air current during the whole process.

4.4 4.4.1

Calculation of Exhaust Velocity and Flow Calculation of Exhaust Velocity

The air velocity Va of the ventilation pipe under the working condition of close to the normal temperature and normal pressure (t = 20 °C, Ba + Ps = 101,300 Pa) is calculated according to formula (1) [6]: pffiffiffiffiffi Va ¼ 1:29Kp Pd

ð1Þ

wherein Va air velocity of ventilation pipeline under normal temperature and normal pressure, m/s; Kp correction coefficient of pitot pipe; Pd exhaust dynamic pressure, Pa; Ba atmospheric pressure, Pa; Ps exhaust static pressure, Pa.

4.4.2

Calculation of Mean Velocity

The mean air velocity Va of a section in the ventilation pipeline under the working condition of close to normal temperature and normal pressure is calculated according to formula (2): Pn Va ¼

i¼1

n

Vai

ð2Þ

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wherein Vai air velocity of a test point, m/s; n number of test points.

4.4.3

Calculation of Exhaust Flow

The air volume Qa in the pipeline under the working condition of normal temperature and normal pressure is calculated according to formula (3): Qa ¼ 3600
F
Va

ð3Þ

wherein Qa airflow in ventilation pipelines, m3/h; F pipeline section area, m2.

5 Conclusion The method and instrument for measuring the pipeline air volume are selected according to the site condition, running status of the ventilation equipment, fan running power, hood face quantity, open degree, etc. The scientific measurement result can only be guaranteed by sufficiently understanding the working condition of the site, mastering the instrument suitability, and ensuring the normal running status of the measurement equipment. The objective assessment and feasible suggestions can only be made by the scientific measurement and comprehensive assessment of the ventilation system in the protection equipment of the sanitary engineering [7, 8]. Acknowledgements This work is supported by the National Key R&D Program of China, Grant No. 2016YFC0801700.

References 1. Liu B-L et al (2018) Risk assessment and control technology of chemical harmful factors. Coal Industry Press, Beijing 2. He C, Liu G, Ren Z, Wang S (2010) Study on risk assessment method of hazardous substances existing in workplaces suitable for mid-small enterprises. J Safety Sci Technol 6(1):94–99 3. Lu Y (2002) Heating, aentilating and air conditioning. China Architecture and Building Press, Beijing 4. Hygienic Standards for the Design of Industrial Enterprises GBZ1-2010

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5. Shao Q, Hu W, Zhang D. Occupational-disease-inductive health engineering control technology. Chemical Industry Press, Beijing 6. Methods for the determination of particulate matter and sampling gaseous pollutants from stationary source exhausts. GB/T16157-1996 7. Su Z et al (2003) Occupational hazard assessment of construction projects. China Population Publishing House, Beijing 8. Hao X, Wang Y, Li K, Fan J (2008) Analysis of specialty capacity of safety assessment personnel. J Safety Sci Technol 4(5):142–145

The Influence on the Limit Flow Ratio Caused by the Change of the Area of the Exhaust Hood Face in the Design of Push–Pull Ventilation Shulin Zhou, Bin Yang and Huijun Zhang

Abstract This study is to investigate whether the change of the exhaust hood area has an effect on the limiting flow ratio KL in an push–pull ventilation device, especially when the face area of the supply hood is larger than the exhaust hood. This research is based on experiment. Set up a push–pull ventilation device, change the area of the exhaust hood face under the condition of maintaining other factors unchanged. Determine the minimum exhaust volume which completely drains the given air supply without overflow by the tracer method, and the KL could be deduced. The experimental results show that under the above experimental conditions, the change of the exhaust hood area will cause a change on the limiting flow ratio KL, and the larger the gap between the supply and exhaust hood area, the greater the KL value will be. Change the distance between the push and pull hood face, repeat the above experiments, it is verified that the conclusions above are still valid when the distance changes.




Keywords Push–pull Ventilation volume rate Flow ratio method





Area of the exhaust hood face
Exhaust

1 Research Purpose The push–pull ventilation device comprises of a supply hood and an exhaust hood. It exhausts the supplied air mixed with harmful substances by delivering the harmful substances to the exhaust hood which then supplies adequate exhausted air amount on the principle that compared with the exhaust process; the supply process has a longer air flow influence distance but slower attenuation [1]. Compared with the local exhaust device, the push–pull ventilation device can save a great amount of air amount [2] and has the advantages of better control of harmful substances,

S. Zhou (&)
B. Yang
H. Zhang China Academy of Safety Science & Technology, Beijing 100029, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_48

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flexible air flow organization forms, effective utilization of work space, no influence on operation process, etc. [3]. It has been widely applied in the processes of electroplating, pickling, and cleaning, and a great quantity of researches have been carried out for its design method in recent years [4]. Foreign researchers have researched the push–pull ventilation since the beginning of the twentieth century but Chinese researchers started relatively late since the 1960s by translating relevant foreign monographs including Factory Ventilation [5] written by Rintaro Mori. Rintaro Mori proposed the calculation method of limit flow ratio for the design calculation of the push–pull exhaust hood and developed the parallel-flow push– pull ventilation device [6]. Rintaro Mori’s research achievements deeply influenced the research of Chinese push–pull ventilation. The push–pull ventilation device is designed as follows: The supplied air carries and sends harmful substances to the exhaust hood which then exhausts the supplied air away. For getting the excellent pollution exhaust effect, totally sucking the supplied air away without overflowing by the exhaust process is one of the preconditions for the performance of the push–pull ventilation system. There are entrainment air currents in the air supplying process; thus, the exhausted air amount shall be larger than the supplied air amount [7]. This phenomenon is described as Qexhausted = (1 + K)Qsupplied in Rintaro Mori’s flow ratio method [8, 9]. Based on the flow ratio method, it shall determine vsupplied in the range of 0–3 m/s (the research doesn’t consider the most economical algorithm of Qsupplied), then calculate the limit flow ratio KL(i.e., the K value when it is going to leak) with a formula according to the parameters of the distance between the supply hood and exhaust hood, the flange width of the blowing outlet, the flange width of the suction inlet, the width of the supplying outlet Dsupply, the velocity of the crosswind and the blown current speed vsupply so as to get Qexhaust when design the parallel-flow push– pull ventilation. At last, determine the width of the exhaust hood in the range of 0:5 5 Dexhaust =Dsupply 5 10, i.e., the width (or area) of the exhaust hood itself is not used as the important influence factor for calculating KL. The article changed the area of the exhaust hood for several times under the precondition that the supplied amount, the distance of the supply hood and pull hood, the flange width of the blowing outlet, the flange width of the suction inlet, the width of the supplying outlet Dsupply, the velocity of the crosswind and the blown current speed vsupply are not changed and judged the minimum exhausted air amount with the tracer method under the precondition that there was no supplying leakage and then reversely deduced KL. The article then judged according to the change of KL. If KL had no change, it means the area (or width) of the exhaust hood had no influence on KL, or else, the area (or width) of the exhaust hood had influence on KL. We further proved the conclusion above by repeating the experiment through changing a variable, such as the supplied air amount, the distance between the supply hood and pull hood so as to verify if the conclusion is not influenced by the corresponding variable changed. The article verified the conclusion above by changing the distance between the supply hood and pull hood for several times.

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In addition, generally, the exhaust hood is larger than the supply hood for effectively capturing the supplying current when the push–pull ventilation device is designed, however, limited by the site condition, sometimes the exhaust hood has to be smaller than the supply hood in actual application. The article names this phenomenon as forced area exchange of the supply and exhaust hood opening. Special attention was paid to the phenomenon in the experiment. The experimental scheme of the forced area exchange of the exhaust hood opening was used when the area of the exhaust hood opening was changed. Thus, the conclusion above is only limited to the precondition of the forced area exchange of the exhaust hood opening.

2 Research Method 2.1

Experiment Condition

The experiment was carried out at the Industrial Ventilation Laboratory of the key laboratory of State Administration of Work Safety. The experiment mainly used the following equipment: supply hood (opening area: 0.7  0.7 m2), exhaust hood (0.7  0.7 m2), 24-point anemometer, Aro-eye (Japan Koken) air amount direct reading device, smoke generator (Dainichi PS-2005), laser pointer, black curtain, etc.

2.2

Test Method

Oppositely put the supply hood and exhaust hood as shown in Fig. 1, the initial areas of the supply hood and exhaust hood were same, and covered the exhaust hood opening with a wooden plate to change the area of the exhaust hood opening; smoked with the smoke generator at the supply hood opening as the air current tracer to develop the air current visualization experiment; projected laser with the laser pointer from the edge of the supply hood opening to the edge of the exhaust hood opening; visually checked was there any smoke exceeding the laser line, if no, it is believed the supplied air current was effectively exhausted, and the supplying and exhausting effects were good. For getting clearer visualization, laid a black cloth on the workbench, and hung a black curtain behind the exhaust hood. It was equivalent as a baffle by hanging the curtain at the edge of the exhaust hood opening, thus, even the area of the exhaust outlet was changed by covering, the change of the baffle area could still be ignored because compared with the curtain area, and the area of the baffle for covering was too small.

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Fig. 1 Schematic diagram of experimental device

The supplied air amount Qsupplied in the experiment was determined as follows: uniformly divided 16 rectangular grids at the supply hood opening, used the multi-point anemometer to measure the velocity at the central points of all rectangular grids, and 100 measurement data were read at each measurement point. Calculated their average value which was used as the velocity of the measurement point, and then calculated the average velocity of the 16 measurement points as the average velocity of the supply hood opening. The product of the average velocity of the supply hood opening and the area of the supply hood opening was Qsupplied. The exhausted air amount Qexhausted was determined by the value which was directly read by the Aro-eye air amount direct reading device which was installed in the exhaust pipeline.

3 Research Process 3.1

Initial Experiment

At first made the area of the exhaust hood and the area of the supply hood same, randomly set the supplied air amount Qsupplied as 0.12 m3/s, and randomly set the distance D between the supply hood opening and the exhaust hood opening as 1.4 m. Adjusted the exhausted air amount and carried out the tracer air current visualization experiment. Observed the exhaust effect and determined the minimum exhaust amount Qexhausted when the good exhaust effect was obtained. Calculated KL. The experiment result showed KL was 2.17.

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Change the Area Ratio Sk of the Exhaust Hood and Supply Hood

Rintaro Mori’s flow ration method set the widths of the exhaust hood and supply hood in the range of 0:5 5 Dexhausted =Dsupplied 5 10, and then the width range in the forced area exchange condition is 0:5 5 Dexhausted =Dsupplied \1, and thus, the forced area exchange range of the supply hood and exhaust hood allowed by the flow ratio method is as follows: 0:25 5 Sk \1;

Sk ¼ Sexhausted =Ssupplied

The area ratio Sk of the exhaust hood and supply hood may exceed the range of 0:25 5 Sk \1 ðSk ¼ Sexhausted =Ssupplied Þ in the actual site (such as the water-curtain painting room) condition of the industrial enterprise, thus, the case of Sk = 1:8 was added in the experiment and tested together. Covered the exhaust hood opening to make Sk be, respectively, 0.5, 0.25, and 0.125. Repeated the experiment above and then Table 1 was obtained.

3.3

Changed the Distance D Between the Supply Hood Opening and Exhaust Hood Opening

The experiment was, respectively, repeated by further changing the distance D between the supply hood and exhaust hood as 1.75 m which is 1.25 times of the initial distance and 2.1 m which is 1.5 times in order to exclude the condition that the conclusion above was achieved at the specific distance D between the supply hood and exhaust hood. The experiment results are shown in Table 2.

Table 1 KL changes with Sk KL D (distance between the push and pull hood face)

Area ratio of the push to the pull hood face Sk1 = 1 Sk2 = 0.5 Sk3 = 0.25 Sk4 = 0.125 1.4 m

2.17

3.05

4.01

4.58

Table 2 KL changes with Sk under various distance between the push and pull hood KL D (distance between the push and pull hood face)

Area ratio of the push to the pull hood face Sk1 = 1 Sk2 = 0.5 Sk3 = 0.25 Sk4 = 0.125 1.4 m 1.75 m 2.1 m

2.17 2.76 3.37

3.05 3.78 4.05

4.01 4.84 5.27

4.58 5.22 6.00

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KL

4.00 D=1.4m 3.00

D=1.75m D=2.1m

2.00 1.00 0.00

0

0.2

0.4

0.6

0.8

1

1.2

Sk Fig. 2 KL Changes with Sk under various distance between the push and pull hood face

4 Research Result Made the data above into a line chart as shown in Fig. 2. It can be clearly judged that the higher the gap of the forced area exchange of the exhaust hood and the supply hood, the higher the KL value will be. The same trend is also displayed even in the condition of Sk = 0.125 which exceeds the range of 0:25 5 Sk \1. This trend is basically the same under the three various D between the supply and exhaust hood. The following formula can be fitted according to the data above: KL ¼ K ¼ 2:196 þ 1:85D  2:916Sk ;

R2 ¼ 0:9317

When the fitting goodness judgment coefficient R2 is higher than 0.9, the goodness of fit is good.

5 Conclusion The experiment verifies that changing the area of the exhaust hood influences KL under the condition of the forced area exchange of the exhaust hood and supply hood when the other conditions are not changed, and the rule does not change with the variation of the distance between the supply hood and exhaust hood. Thus, we shall not ignore the influence of the exhaust hood area on the whole supplying and exhausting coupling function when design the push–pull ventilation system, particularly the forced area exchange of the supply hood and exhaust hood. It may not reach the best supplying and exhausting coupling effect only with the

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supplied air amount and the system exhausted air amount which is determined according to KL calculated out by the flow ratio formula. Besides the experiment above, the research also checked if KL will be influenced by changing Sk under all conditions in which Qsupplied is given by changing the supplied air amount Qsupplied. The results are same to the result of the experiment above. Acknowledgements This study was supported by the National Key R&D Program of China, Grant No. 2016YFC0801700.

References 1. American Conference of Governmental Industrial Hygienists (2010) Industrial ventilation a manual of recommended practice. ACGIH, Cincinnati 2. Malin BS (1945) Practical pointers on industrial exhaust system. Heat Vent 42:75–82 3. Tuyosi Y, Katsurou O, Kumasi N (2013) The standard design and maintenance management of local ventilation push- pull ventilator and air cleaner. Japan Ind Safety Health Assoc, Tokyo 4. Guo P, Fu H, Zhao Y et al (2008) Development and present status of push-pull ventilation technology. J Heating Vent Air Conditioning 38(4):57–61 5. Tarou H (1986) Factory ventilation. China Architect Building Press, Beijing 6. Zheng W, Wang Y, Tang Y (2011) Status of researches and applications of push-pull ventilation technology. HV&AC 47(4):1–5 7. Damin Z, Tsuji K, F Isamu (1987) Simulations of the push-pull flow. Air Conditioning Pap Collect Soc Health Eng 33:33 8. Tarou H, Howell RH, Makoto S et al (1988) Industrial ventilation and air conditioning. Beijing Industrial University Press, Beijing 9. Sakurai H, Kanehara K, Fukuhara I et al (2000) Proposal of a simplified equation for push-pull type local ventilation systems. Sci Labour 76(6):261–268

Research on the Environment Character

Simulation and Analysis of Sun Illumination on a Satellite Na Zheng, Haoting Liu, Weidong Dong, Shuo Yang and Shunliang Pan

Abstract A mathematical and emulational model of the solar illumination obtained from a satellite is proposed. First, the sunlight received on the surface of the satellite is analyzed. Second, three models are essential for simulation: the satellite model, the orbit model, and the solar energy model. The satellite model is a kind of simplified satellites, which is constructed to provide the corresponding geometry. To be precise, the orbit model is a sun-synchronous orbit. The solar energy model is suitable for most satellite models and orbit models. Third, the time of illumination and the value of the solar vector in the satellite coordinate system are substituted into the solar energy model. Last, data maps of the satellite’s solar energy are generated. After a large number of experiments, the effect of the theory has met the application requirements. Keywords Solar energy


Solar illumination
Sun-synchronous orbit satellite

1 Introduction Sunlight is the most influential light in satellite’s orbital motion. At the same time, solar illumination can provide solar energy to satellites, and it also affects the operation of certain image recognition algorithms on satellites. Therefore, solar illumination is very important for the study of an orbiting satellite. At present, for the simulation of space lighting scenes, there are mainly the following research directions [1]. First, based on the simple texture mapping, the mathematical modeling method is used to simulate the implementation. Second, the running dynamics of the sun, earth, and satellite are simulated, and then simulated lighting is used to N. Zheng
H. Liu (&) Beijing Engineering Research Center of Industrial Spectrum Imaging, University of Science and Technology Beijing, Beijing 100083, China e-mail: [email protected] W. Dong
S. Yang
S. Pan Institute of Manned Space System Engineering, Beijing 100094, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_49

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achieve equivalent simulation of the lighting environment. Third, according to the scattering effect of the Earth’s atmosphere, the realistic simulation of atmospheric halo is carried out by using the Mie scattering formula and the Rayleigh scattering formula. Xiang [2] brought the size and the lighting time of the satellite into the calculation formula to obtain the direct solar radiation, so as to conduct a theoretical analysis of the direct solar radiation on the satellite’s surface. According to the track and posture condition, Chen [3] calculated the incident angle of solar light during the orbit operation of the spacecraft and analyzed the change of the incident angle of sunlight. The existing researches have restored the space scene to some extent, but they do not take into account the relative particularity of the space illumination environment and the different effects of the satellites’ attitudes. It is necessary to establish a more general method to analyze. In this case, this paper proposes a mathematical and emulational model of the solar energy obtained from a satellite.

2 Method 2.1

Proposed Flowchart

Taking the satellite at low orbit as an example [4, 5], the illumination of natural light sources such as the sun, the earth, the moon, the cosmic light, the starlight, and the galaxy will affect the satellite. In the cosmic environment, sunlight is the main source of light, and other sources are negligible. The data processing can be established to implement illumination analysis. In Fig. 1, the satellite model, the orbit model, and the solar energy model are applied, respectively. First, the position and attitude of the satellite are entered. Second, according to the actual situation, the required satellite model and orbit model are established. Third, the sun vector at the current position and attitude is calculated for subsequent use. Fourth, some formulas are derived to establish a solar energy model and both the previously obtained parameters and the sun exposure parameters are brought into it. Finally, the solar light analysis can be performed. In addition to this, based on the intensity of solar radiation, the analysis of solar energy is finally performed.

2.2

Satellite Model

The target star is set to a sun-synchronous orbit satellite. A sun-synchronous orbit (SSO, also known as a heliosynchronous orbit) is a near-polar orbit around a planet. This satellite passes over any given point on the surface of the planet at the same

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Fig. 1 Data processing flow for solar illumination analysis

local average solar time. Besides, this satellite always maintains the same relationship with the sun. The satellites have many different irregularities. Under these circumstances, the satellite model uses a simplified model and the outer surface of the satellite is divided into multiple simple surfaces. Figure 2 is a vector diagram of a satellite model. The shape of the satellite is set to a cylinder, which is the basic shape of most satellites. The base of the satellite has a diameter of 10 m and a height of 20 m. The red vector represents the sunlight vector. As the satellite is far from the sun, sunlight can be reduced to parallel light. Since the position of the sun vector and the satellite is constantly changing, the energy obtained by the satellite is also different. The specific content will be analyzed in the solar energy model.

2.3

Orbit Model

Different types of satellites have different orbits [6]. Because typical SSO is used, the parameters of the orbital model have a certain pattern. According to the characteristics of SSO, the following settings are applied. Both of apogee radius and perigee radius are 6778.14 km. Eccentricity is 0. Inclination is 97.0346 deg. True anomaly and mean anomaly is 0 deg. A vector model of satellite and illumination is represented by using an in-track/gross-track/radial (ICR) coordinate system. The coordinate system is indicated in Fig. 3.

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Fig. 2 Satellite model vector

Fig. 3 Satellite trajectory and satellite coordinate system

The origin of the Cartesian coordinate system is the centroid of the satellite model. The +x-direction is located in the track where the satellite is flying. It lies in the orbital plane and perpendicular to the z-axis. The +y-direction is cross-track. The +z-direction is radial. The center of mass points to the direction of the center of the earth. The orbital model determines the trajectory of the satellite’s operation and the characteristics of the solar vector’s variation in the ICR coordinate system.

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431

Solar Energy Model

The solar energy model can calculate the amount of solar energy obtained by the satellite in real time. The amount of solar energy can be obtained by bringing the relevant parameters into the following derived formula. The solar vector can be expressed in the satellite coordinate system as: ~ S ¼ ðcos a; cos b; cos cÞ

ð1Þ

where a, b, c are the angles between the ~ S and the +x-, +y-, and +z-axes, respectively. Unit vector of a point on the satellite surface is: 0 0 !   ru ðu; vÞ  ! rv ðu; vÞ
¼ dx ; dy ; dz ~ n ¼

0 0
ru ðu; vÞ  ! rv ðu; vÞ

!

ð2Þ

S and ~ n is where, dx ; dy ; dz 2 ½0; 1 and dx2 þ dy2 þ dz2 ¼ 1. The angle between ~ recorded as hðu; vÞ. Solar radiation intensity is considered as the average information L. So, solar radiation received by every point can be presented as: ZZ P¼L

cos hs ðu; vÞ þ jcos hs ðu; vÞj dudv 2

ð3Þ

Equation (3) calculates the total amount of solar energy on the surface of the object by adding the integral of the solar energy per unit.

3 Experiments Some experiments were conducted to verify the validity of the theory. The computer hardware configuration for the experiment is Intel® Core™ i5-4200H CPU @ 2.80GHz. There are two major steps. The first step is to apply the simulation software to capture the angle between the sun and the ICR coordinate system. The second step is to bring the real-time angles and other parameters into the solar energy model and calculate the solar energy data. Through the above two steps, the final amount of solar energy can be calculated.

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Fig. 4 Angles between the sun vector and the ICR coordinate system

3.1

Simulation Results of Angle Between Sun Vector and Coordinate System

The relative position of the sun and the satellite is changing at all times, so the angles between the sun vector and the coordinate system are constantly altering. These angles are important for the calculation of the subsequent solar energy model. Through the simulation, the angles between the ~ S and the three coordinate axes in the ICR coordinate system can be obtained as shown in Fig. 4. The blue line represents the angle between the sun and the x-axis. The orange line represents the angle between the sun and the y-axis. The gray line represents the angle between the sun and the z-axis. From the data, it is obvious that the angle between the sun vector and the y-axis is almost constant. This is determined by the characteristics of the SSO satellite, which also simplifies the calculation of solar energy. The above operation can get information about the angles.

3.2

Solar Energy Simulation Results of Typical Satellite Surface

Through the previous step, we have obtained the change of the angles between the sun vector and the coordinate axis. In addition, by consulting the data, the relevant solar illumination parameters are obtained. After the parameters are brought into the solar energy model, the relevant conclusions can be gradually derived. As is well known, the cylinder has upper and lower bottom surfaces as well as side surfaces. The top and bottom are discussed together, and the sides are discussed separately, which is much simpler. Since the shape of the satellite is cylindrical in the satellite model, the top and bottom surfaces of the satellite are round and constant. After using Eq. (3), some data can be shown in Fig. 5. The horizontal axis of the data is time, and the vertical axis of the data is the amount of solar energy. The two peaks are, respectively, the solar energy obtained by the top and the bottom of the satellite.

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Fig. 5 Top and the bottom of the cylindrical satellite get solar energy

Fig. 6 Curve surface of the cylindrical satellite get solar energy

The satellite model has been built, and it is a cylinder. In the satellite model, in addition to the top and the bottom of the cylindrical satellite, the side of the satellite is also important. The side of the satellite is a complete curve surface. Because the curved surface of the surface is larger than the top and the bottom of the satellite, the surface can capture more solar energy. This can also be reflected in Fig. 6. The other side of the satellite is a curved surface except that the top and bottom surfaces are round and constant. After using Eq. (3), some data can be shown in Fig. 6. In Fig. 6, the abscissa represents time, and the ordinate is the power obtained by the satellite. Obviously, the solar energy that the surface of the satellite obtained is also periodic. When the amount of solar energy is zero, the surface does not receive the sun’s illumination. This phenomenon can be used to adjust the opening and closing time of the solar cell.

4 Discussions The satellite plays an important role in the modern society, and China has made ambitious plan to develop her in-orbit service technique in the near future; however, the sunlight is an inevitable variable in the satellite environment. This paper is aimed at the future requirements of space station services and carries out research on simulation modeling technology of in-orbit satellite’s solar environment.

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This experiment carried out the simulation of the sunlight obtained by the satellite and finally established the solar energy model. The advantage of this model is that it can generate corresponding solar energy data by referring to the continuously adjusted attitude of the satellite. The model still has shortcomings. For example, the solar energy model relies heavily on the accuracy of the sun’s illumination parameters. Once the sun’s illumination parameters are different, the correctness of the model has certain risks. In the future, the research direction is to improve universality, making the simulation model suitable for more complex situations. The on-orbit solar environment is an environment with instability, variability, and high risk. At the same time, working in orbit has important implications. Therefore, it is very important to further improve the stability of the solar energy analysis model.

5 Conclusion This paper gives an expression and model of the satellite’s solar energy. In addition, the application method and correctness of the solar energy simulation are demonstrated by applying a certain satellite model and orbit model. In the simulation process, the satellite model, the orbit model, and the solar energy model are proposed. The satellite model and the orbit model can be replaced according to the application conditions. The solar energy model is derived from the formula. After the relevant parameters are brought into the solar energy model, a more specific solar energy application can be carried out. After experiments, the simulation model works well. Acknowledgements This work is supported by the National Nature Science Foundation of China under Grant No. 61501016 and the open project of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect under Grant No. SKLIPR1713.

References 1. Liu X, Chao J, He N (2011) Study on the illumination simulation method for visual simulation of the space flight training simulator. J Astronautics 32:2622–2627 2. Xiang S, Zhang T (2007) Calculation of solar direct radiation on the satellite external surface using STK. Infrared Technol 29:508–511 3. Chen G, Zhang Z, Liao Y (2012) Modeling and simulation analysis of solar illumination angle on spacecraft solar wing in-orbit. Spacecraft Engineering 21:37–42 4. Wang J, Li M (2018) Satellite analysis of sun-synchronous orbit. Technol Innov Appl 22:26–27 5. Dai G, Liu Q (2011) Modeling and simulation of the Near—earth space scene. Comput Simul 28:26–30 6. Wang G, Xing F, Wei M et al (2017) Optimization method of star tracker orientation for sun-synchronous orbit based on space light distribution. Appl Opt 56:4480–4490

Control Logic Design Based on Modeling of Aircraft Cockpit Temperature Control System Yudi Liu, Chengyun Wu, Zhiyong Min and Xuhan Zhang

Abstract Cockpit temperature control system is an important part of the environment control system (ECS) which will directly impact the health and comfort of the pilot. This investigation built the physical model for the cockpit temperature control system of one real aircraft in commercial software, Matlab Simulink. Experimental data of the aircraft cockpit rapid cooling test was used to verify the model. The simulated cockpit temperature curve agrees with the experimental data. The verified model was then used to implement the control logic design based on both PID and cascade control theory. The comparison of these two control logic shows that cascade-PID has a better dynamic response when controlling the cockpit temperature of aircraft with a lower overshoot of 0.12 °C and a shorter settling time of 48 s. The results also show that during a rapid cooling condition, control logic has no impact on the variation trend of cockpit temperature. Keywords Cockpit temperature control system Cascade control


Modeling
Aircraft
PID


1 Introduction Cockpit temperature of aircraft mainly depends on the heat load and supply air temperature. Temperature of supply air is regulated using the trim air valve (TAV) of the cockpit temperature control system (CTCS). CTCS should respond quickly to the change of external environment and condition of supply air in order to keep the cockpit temperature within a certain comfortable range. A well-designed CTCS control logic is an important factor for the competitiveness of a commercial aircraft. It is essential to find out a method to design the control logic of CTCS based on engineering.

Y. Liu (&)
C. Wu
Z. Min
X. Zhang Shanghai Aircraft Design and Research Institute of COMAC, Shanghai 201210, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_50

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Cockpit is one kind of large space with quite an amount of airflow, the temperature variation in which is a process with large inertia and nonlinear features. As the design of control logic needs iterations, design based on hardware may not only cost a large amount of time and human resources but also do harm to the component due to incomplete consideration at the beginning. Thus, design with simulation model is chosen as a suitable method. In recent decades, there have been many studies on the temperature control system of aircraft. Most of the investigations focused on passengers’ comfort and take the cabin as the object. The researchers used advanced control theories including fuzzy control [1–4], neural network algorithm [5], and expert-PID decoupling control [6] instead of traditional PID control method to find out new intelligent cabin temperature control logic. All these studies placed emphasis on the design of control logic and ignored the model building and verification. Zhou et al. employed a digital PID controller to regulate cockpit temperature, but the paper did not explain the detail of the design process [7]. Besides, other investigations have studied the relationship between ECS and cabin temperature, such as Romani and de Góes [8], and Yin et al. [9]. A number of researchers also have studied spaces similar to the cockpit. These investigations used cascade-Smith predictive control [10], DMC control [11], or DMC-PID control [12] to compare the control quality with traditional control methods. For Smith predictive control and DMC control, it is not executable during early design of an aircraft in lack of necessary inputs. As for fuzzy control, due to the fuzzy processing of information and nonsystem state of the design cycle, it still needs development to be applied in an aircraft. Considering the reliability requirement of CTCS on aircraft, the researchers are devoted to finding out engineering verified control logic for CTCS with simple structure. This paper reports the effort in developing a physical simulation CTCS model of one real commercial aircraft. The model is verified with experimental data during the rapid cooling test. Then by use of the verified model, this study developed two traditional control methods including PID and cascade-PID to find out a better control logic for engineering design of CTCS on aircraft.

2 Model Building To build the CTCS model, this research firstly drew the schematic diagram for a commercial aircraft. As shown in Fig. 1, CTCS contains six main parts, which are trim air duct, cooling air duct, mixing point, temperature sensor, and cockpit. When regulating the cockpit temperature, the controller compares the actual temperature in the cockpit and the setting point to adjust the angle of TAV for the regulation of flow with high temperature from the trim air system.

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The architecture of the simulation model for CTCS was defined according to Fig. 1, and the model was built in Matlab Simulink, commercial software for simulating control logic design. The simulation model consists of four main parts including TAV model, duct thermal model, cockpit thermal balance model, and TAV controller model. TAV is a butterfly valve controlled by a stepper motor. When it is in operation, the valve receives an electrical signal from the controller to calculate the opening angle. Functional TAV model was built considering the operating principle. The model firstly transfers controller signal to valve opening angle and then uses a valve opening angle transfer function to get the real dynamic feature. Flow out of the valve is calculated using the angle and upstream parameters. The internal structure of TAV is shown in Fig. 2. All the ducts in CTCS share the same structure of three layers, namely duct wall, air gap, and insulation. This study built a general duct thermal model using S-function in Matlab Simulink. The duct model is a combination of duct thermal model for each part. This investigation took all the thermal process into consideration for accuracy including forced convection inside the duct, heat conduction inside the duct wall, heat conduction and radiation within air gap, heat conduction inside insulation and heat convection, and radiation between the outer surface of insulation and environment. The crucial thermal parameters, in general duct thermal model, were calculated with the following equations.

Fig. 1 CTCS schematic diagram

Fig. 2 Model structure of TAV

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Natural-convection heat transfer coefficient H is determined with Eq. 1:  0:25 DT H ¼ 2:51  C  L

ð1Þ

where C and L are factors related to duct direction, and DT is the temperature difference. For horizontal circular duct, the value of C is 0.52, and L is the diameter [13]. Forced-convection heat transfer coefficient Hf is calculated referring to Eq. 2 [14]. Hf ¼ Nu 

k d

ð2Þ

where k is heat conductivity coefficient of air; d is the diameter of duct; and Nu is the Nusselt number. Heat conductivity coefficient of air is determined through Eq. 3.   jðt  273Þ  250j  9:5 k ¼ 0:53  ðt  273Þ þ 214:5   104 250

ð3Þ

where t is the airflow temperature. Nusselt number is defined with Eq. 4. l¼

  8:5ðt  273  200Þ  107 0:3875  ðt  273Þ þ 180:5  200

ð4Þ

where t is the airflow temperature. Cockpit thermal balance model is the most important part of the controlled object, whose accuracy will largely affect the design of control logic. This study considered the impact of heat transfer through skin, sun radiation, heat dissipation from electronic equipment and human inside, and the heat transfer between furniture and air to set up the thermal balance equation as Eq. 5. Czone mzone DTzone ¼ Qsup þ Qsun þ Qelec þ Qpax þ Qwall þ Qfur

ð5Þ

where Czone is specific heat of air; mzone is mass of air inside cockpit; DTzone is the temperature variation inside cockpit; Qsup is heat of supply air; Qsun is heat of sun radiation; Qelec is thermal load of electronic equipment; Qpas is human body heat loss; Qwall is heat exchange through skin; and Qfur is heat exchange with furniture, which is equal to zero in steady condition. This research used the experimental data of a commercial aircraft under the rapid cooling condition to verify the cockpit thermal balance model. The initial temperature inside the cockpit was 40 °C, and the setting point of CTCS is 24 °C. The supply air parameters used during verifying came from the temperature sensor

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Fig. 3 Verification of cockpit thermal balance model

installed on the commercial aircraft. Figure 3 is the comparison of simulated and measured cockpit temperature varying with time. The simulated air temperature in the cockpit agrees well with the experimental data.

3 Design of Control Logic This study designed PID and cascade-PID controller using Matlab App box. The parameters are shown in this section. CTCS with PID control logic takes data of cockpit temperature sensor as the input of the controller. The controller regulates the opening angle of TAV depending on the difference between measured cockpit temperature and the setting point. Figure 4 shows the structure and final parameters of PID controller model. Figure 5 is the structure of cascade-PID controller model. In order to avoid errors, this study added an initial value for the master controller. The initial value is suggested to be within the range of controlled object variation.

Fig. 4 Structure of PID controller model

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Fig. 5 Structure of cascade-PID controller model

4 Discussion There are four principles during the design of CTCS in commercial aircraft, namely 1. The CTCS should have the ability to cool the cockpit temperature to 27 °C within 30 min under hot day condition on the ground. 2. The regulating time should be as short as possible. 3. There should be no sensible overshoot during the regulation. 4. No steady-state error should exist when the temperature is steady. This investigation selected better control logic for commercial aircraft based on the principles. Figure 6 shows the dynamic response curve of cockpit temperature under PID control with the setting point stepping from 27 to 35 °C. The environment temperature was 40 °C, and there were two crew members in the cockpit. It takes about 130 s for the cockpit temperature to reach the error band of ±2 °C. During the adjustment, the largest overshoot is close to 2 °C. When the cockpit temperature achieved stability, there is no difference between the steady temperature and setting point.

Fig. 6 Dynamic response curve of PID control

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Fig. 7 Dynamic response curve of cascade-PID control

Table 1 Dynamic response of CTCS Control method

Regulating time (s)

Overshoot (°C)

Steady-state error (°C)

PID Cascade-PID

130 48

2 0.12

0 0

The performance of cascade-PID control is found in Fig. 7. The environmental conditions were the same as PID control. The regulation time is about 48 s, which is shorter than half of that under PID control. The overshoot in Fig. 7 is nearly indistinguishable. The steady-state performance is as good as PID control with no error after regulation. In order to evaluate the performance visually, Table 1 shows three important parameters of these two control logic under the same operating condition. According to Table 1, both kinds of control logic have no steady-state error, which means the dynamic response is the main criteria of better control logic. It is obvious that cascade-PID control has a better ability with shorter regulating time and smaller overshoot. This paper used the experimental cockpit temperature of a commercial aircraft during rapid cooling to verify the simulating model. Figure 8 is the comparison of simulated and measured cockpit temperature variation with the setting point of 24 °C. The result shows that during rapid cooling, the variation trends of cockpit temperature are similar. The difference at the same moment is smaller than 1 °C, which could be neglected. Both control logic could meet the requirements of CTCS with 1700 s for cockpit temperature to reach 27 °C and 3400 s to 24 °C. The reason is that the initial cockpit temperature is much higher than the setting point. The CTCS is required to cool the cockpit as soon as possible, which means the system needs to keep the supply air at the lowest temperature. Therefore, TAV is

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Fig. 8 Comparison of simulated and measured cockpit temperature variation

required to be full closed during the rapid cooling condition, and temperature variation is only related to the largest cooling ability of ECS. As cooling ability has nothing to do with control logic, the temperature variation during rapid cooling is similar under both PID and cascade-PID control. The green line in Fig. 8 is the experimental cockpit temperature of the commercial aircraft during rapid cooling. The simulated lines agree well with the green line. The deviation at the beginning is because the gradual cooling of supply air during experiment makes it slower to cool the cockpit. There is a difference of about 1–2 °C after 3000 s, which may be caused by the undulation of the environment and supply air conditions during the test. Considering the deviations mentioned before are unavoidable and nonsignificant, the model built in this investigation is able to simulate the CTCS of aircraft accurately.

5 Conclusion This study built the simulation model of CTCS based on the parameters of one real commercial aircraft and simulated the performance of PID control and cascade-PID control. Then, the model and simulated cockpit temperature were verified with experimental data under a rapid cooling condition. Three conclusions have been drawn through this investigation, which are: 1. The model built in this study is able to simulate the cockpit temperature variation accurately. 2. The temperature variation in cockpit during rapid cooling is only based on the largest cooling ability of ECS. 3. Cascade-PID control is suitable for CTCS of aircraft considering the technical maturity, structure, and performance.

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References 1. Tu Y, Lin G (2011) Simulation of large-scale aircraft cabin temperature control system. Acta Aeronautica et Astronautica Sinica 32:49–57 (in Chinese) 2. Tu Y, Lin G (2011) Dynamic simulation of aircraft environmental control system based on flowmaster. J Aircraft 48(6):2031–2041 3. Zhang J, Hao G, Zhang J (2013) Cabin temperature control system simulation of transportation aircraft. In: Proceedings of the 2013 third international conference on instrumentation, measurement, computer, communication and control. IEEE 4. Dobrescu E, Balazinski M (2004) Fuzzy logic aircraft environment controller. In: IEEE meeting of the fuzzy information, processing NAFIPS 04 5. Zuo Q (2017) Investigation of modeling and simulation of cabin temperature control system in jumbo passenger jet. Civil Aviation University of China (in Chinese) 6. Ren M, Wang J, Li R et al (2017) Control law design for temperature control system of large-scale aircraft cabin. Acta Aeronautica et Astronautica Sinica 38(S1):14–22 (in Chinese) 7. Zhou T, Dong J, Song Z (2013) The application study of digital PID controller in cockpit temperature auto-regulating system. Ind Control Appl 32(11):43–44 (in Chinese) 8. Romani R, de Góes LC (2012) Cabin temperature control model for commercial aircraft. In: AIAA modeling and simulation technologies conference, guidance, navigation, and control and co-located conferences 9. Yin H, Shen X, Huang Y et al (2016) Modeling dynamic responses of aircraft environmental control systems by coupling with cabin thermal environment simulations. Build Simul 9 (4):459–468 10. Zhang C, Zhang Z (2016) Modeling and simulation of temperature large time delay cascade-Smith predictive control system. Sci Technol Vis 8:278–280 (in Chinese) 11. Gao X (2013) Research on room temperature control strategy for central heating system. Zhejiang University (in Chinese) 12. Fu Y (2007) Research on large temperature difference supply air of high accuracy constant temperature air conditioning system based on DMC-PID cascade control. Tongji University (in Chinese) 13. Kunimine N (2018) Thermal design lecture-Natural convection and forced convection with calculation example. http://www.360doc.cn/article/34412976_778697044.html 14. Zhang X, Ren Z, Mei F (2007) Heat transfer. China Architecture & Building Press, Beijing

Simulation Method of Jamming Performance of Projectile-Carried Communication Jammer Based on OPNET Platform Lizhi Qian, Jie Zhang and Dong Chen

Abstract Taking the broadband sweep mode as an example, the jamming mode is sawtooth wave plus Gauss white noise. This paper summarized and combed the methods and steps of how to simulate the jamming performance of projectilecarried communication jammer under OPNET platform from three aspects: jammer model construction, jammed node model construction, and different simulation scenarios construction. At the same time, the jamming process and jamming effect of jammers could be simulated and compared from three aspects: building different user sizes, designing different movement modes of jammers and jammed nodes, and different battlefield environments. The system performance was analyzed by collecting the above statistical results. Keywords Projectile-carried communication jammer Simulation OPNET





Jamming performance


1 Introduction The projectile-carried communication jammer is a kind of communication device which is launched by artillery or rockets and uses the projectile as a carrier to carry the jammer to the enemy target area quickly to complete the communication jamming task [1–3]. Figure 1 shows the brief workflow [1]. Among them, the suspension-type jamming projectile can be suspended over the enemy’s target to achieve the close-in jamming, and it is free from terrain restriction. Compared with the ground jamming, it can obtain distance advantage and lift-off gain and achieve a larger jamming range and intensity with a smaller power. At the same time, because of the small size and high-speed flight, the enemy cannot intercept it. Compared with other similar jamming equipment, it is easy to be L. Qian
J. Zhang (&)
D. Chen High Overload Ammunition Guidance and Control and Information Perception Laboratory, Army Academy of Artillery and Air Defense, Hefei 230031, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_51

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Fig. 1 Brief workflow of projectile-carried communication jammer

largely issued. For its unmanned operation, it can avoid casualties and accord with the concept of modern war [1].

2 OPNET Simulation Platform OPNET modeler provides developers with an integrated environment for modeling, simulation, and analysis, greatly reducing the workload of programming and data analysis with its superior flexibility for the design and research of communication networks, equipment, protocols, and applications [4, 5]. As shown in Figs. 2, 3, 4 and 5.

Fig. 2 OPNET software interface

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Fig. 3 Network model

Fig. 4 Process model

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Fig. 5 Interface of technical and tactical parameters for transmitter

3 OPNET-Based Jamming Performance Simulation of Projectile-Carried Communication Jammer Taking the sweep blocking jamming as an example [6], a kind of jamming signal generated by noise source and sawtooth wave generator modulated by voltage controlled oscillator is introduced. As shown in Fig. 6,

Fig. 6 Block diagram of sweep blocking jammer

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Construction of Sawtooth Wave Jammer Model

The model includes jamming signal generating module and jamming signal transmitting module.

3.1.1

Jamming Signal Generation Module

According to the configuration parameters of each jamming signal, such as message size, generation-time interval of jamming message, jamming message format, jamming start time, termination time, or other termination conditions, the corresponding jamming message is generated and sent to the jamming signal transmitting module. The model parameters can be generated according to the specified probability distribution function. The module can count the sending flow of the jamming signal and so on.

3.1.2

Jamming Signal Transmitting Module

According to the configuration parameters such as jamming power, frequency band, sweep interval time, frequency points, modulation and coding mode, transmission bandwidth and signal jamming range, the generated jamming signal message is sent periodically at different frequency points to realize sweep jamming to the whole jamming frequency band, and the number of jamming nodes and the proportion of jamming users can be counted.

3.2

Construction of Jammed Model

The model includes application service message receiving and sending module, MAC layer wireless access module, and wireless transceiver module.

3.2.1

Application Service Message Receiving and Sending Module

According to the generation rule of application services, corresponding service data messages are generated according to the configuration parameters such as the size of service messages, the generation time interval of messages, message format, sending start time, and termination time. They are sent to the MAC access module and receive the service messages sent by other nodes for performance statistics. The module can count the transmission throughput, reception throughput, and end-to-end delay of service messages.

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MAC Layer Wireless Access Module

According to the wireless channel access mode used by the jammed model, the module designs an access mechanism based on TDMA or CSMA to transmit and receive data. If the TDMA mechanism is adopted, the slot size, time element, number of time frames and slots, slot allocation priority of nodes, and load size of the TDMA can be configured. If the CSMA access mechanism is adopted, the competition backoff time of the nodes and the size of the business load that can be carried can be configured. In addition, if the jammed model has frequency hopping mode, the module can control the wireless transceiver module for frequency hopping communication according to the configuration of frequency hopping time interval, frequency hopping range and frequency hopping period. The module can count the throughput, end-to-end delay, channel access delay, delivery rate, and spectrum utilization of the MAC layer.

3.2.3

Wireless Transceiver Module

According to the configuration parameters of signal transmission power, communication frequency range, frequency points, modulation and coding mode (such as 2FSK, 2DPSK, 2PSK, MSK, GMSK) and transmission bandwidth, the module transmits and receives the service signal messages to be transmitted at the corresponding frequency points. At the same time, the receiver module receives the service signal message, calculates whether the jamming signal message collides with the application service message, and adds the jamming operation of Gauss white noise. Based on the received power of the service message, the received power of the jamming signal and the Gauss white noise, the SINR of the received signal is calculated synthetically to determine whether the service signal can receive and demodulate successfully. The module can count the throughput, signal-to-noise ratio, packet loss rate, bit error rate, and channel utilization of the wireless transceiver module.

3.3

Construction of Jamming Simulation Scenario

Constructing communication simulation scenarios with different user sizes, designing different motion modes of jammers and jammed nodes, simulating the motion laws of the above nodes by manually drawing the motion trajectories of the nodes, or setting the nodes to move in the specified direction and speed, and simulating and comparing the jamming process and jamming effects of jammers in different scenarios. By collecting the above statistical results, the performance of the system is compared and analyzed.

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References 1. Qian L (2004) Suspending communication jamming projectile. Artillery Academy, pp 1–13 2. Yang Y, Wang D (1998) Bulgarian communication jamming projectile. Foreign Electronic Warfare, No. 2, pp 38–42 3. Sun M, Huang G (2003) Communication jamming projectile-special projectile for communication jamming. Modern Military, No. 1, pp 39–40 4. Zhou X (2010) Summarization and application analysis of some mainstream network simulation software. http://www.360doc.com/content/10/1118/20/1412590_70524052.shtml. Cited 18 Nov 2010 5. Zhang M, Dou H, Chang C (2007) OPNET modeler and network simulation. People’s Posts and Telecommunications Press, Beijing, pp 9–10 6. Wang M (1999) Principle of communication countermeasure. PLA Press, Beijing, pp 392–393

Experimental Study of Intelligent Lighting Control Method for Dark Field Surveillance Haoting Liu, Chang Guo, Shuo Yang, Weidong Dong and Shunliang Pan

Abstract A kind of intelligent lighting control method for the dark field surveillance is proposed. The design of it includes an offline stage and an online stage. Regarding the offline stage, first a visual ergonomic experiment is used to accumulate image datasets which have different subjective image quality evaluation degrees (IQEDs) for the typical surveillance application. Second, the objective IQED metrics are computed for these datasets above: the image region contrast, the image edge blur, the image gray deviation, and the image noise. Third, the k-means cluster method is employed to analyze the distribution thresholds of the objective metrics. Regarding the online stage, first the objective IQED metrics are computed for the input image. Then, the computed objective results will be compared with the distribution thresholds gotten in the offline stage. Finally, a kind of optimal lighting control will be performed. A lighting experimental system is built, and many experimental results have verified the correctness of the proposed method.




Keywords Intelligent lighting Visual ergonomics Image quality Feedback control





Dark field surveillance


1 Introduction The charge-coupled device (CCD) camera has been wildly used in the fields of surveillance [1]. The CCD camera can get the data with abundant detail, vivid color, and intuitive image; however, its output is always affected seriously by the complex light [2]. The over weak or strong light will make its visual output effect H. Liu (&)
C. Guo School of Automation and Electrical Engineering, Beijing Engineering Research Center of Industrial Spectrum Imaging, University of Science and Technology Beijing, Beijing 100083, China e-mail: [email protected] S. Yang
W. Dong
S. Pan Institute of Manned Space System Engineering, Beijing 100094, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_52

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decreased distinctly. Regarding the surveillance for the dark field, the design of its system cannot leave the lighting device. The lighting device can provide the necessary environment luminance for camera, and the clear image is surely easy for watching and computation. Currently, the light-emitting diode (LED) lamp has been widely used in the municipal works [3]. As a supplement device, the LED has many merits for camera application, such as its small size, its long life, and its low power dissipation. Particularly, the output intensity of LED can be controlled by circuit which makes it more intelligent than the traditional lighting lamp. In this paper, a kind of intelligent lighting control method is proposed. It includes an offline stage and an online stage. When performing the offline stage, first a series of typical image datasets with different subjective image quality evaluation degrees (IQEDs) are accumulated by the ergonomic experiment [4]. Second, some objective IQED metrics [5] are computed for the datasets above: the image region contrast, the image edge blur, the image gray deviation, and the image noise. Third, the distribution thresholds of these metrics above are estimated by the k-means method [6]. Regarding the online stage, first the objective metrics are calculated for the input image. Second, its imaging effect will be assessed by the comparison between the computed metrics and the distribution thresholds. Third, a kind of lighting control [7] will be carried out to improve the lighting effect.

2 Problem Formulation of the Lighting System Without loss of generality, let us take the surveillance application in the intersection as the research prototype. Figure 1 shows the sketch map. Four streetlights are placed behind the zebra crossings at the corner of streets. The surveillance cameras can be fixed beside the streetlights. For the sake of simplicity, let us only take one camera as the research target. The design aim of intelligent lighting system is to tune the output intensity of four streetlights to guarantee the imaging definition of camera to fulfill the observation request of user. In general, the user wants the output of camera to be clear and full of details. In this application, it is supposed that four streetlights are the same and the output intensities of them have three

Fig. 1 Sketch map of the surveillance application in the intersection

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typical degrees, e.g., degree 1 to degree 3. The larger the number is, the stronger the output intensity of streetlight should be. Then, the problem is how to control the output intensities of four streetlights so that the output of camera can be clear.

3 Proposed Intelligent Lighting Control Method 3.1

Implementation Flow Chart

Figure 2 shows the implementation flow chart of the proposed lighting control method. Two implementation stages are utilized in this method. Since the design target is to control the streetlights to provide a friendly lighting environment for the camera, both the subjective and the objective image quality evaluation methods are utilized here. The use of subjective image quality evaluation is to provide the following computation a human factor-related benchmark, while the objective evaluation will give the following computation the actual control variables. As a result, in Fig. 2, the ergonomic experiment will be employed to build the image datasets with different subjective IQEDs; the objective IQED metrics are utilized to learn the distribution thresholds of the subjective IQEDs in quantification and provide a control reference for the following optimal lighting tuning.

3.2

The Offline Stage

An ergonomic method is used to build the benchmark for the following computation. It asks subjects to classify the typical image datasets captured from the intersection scene into three degrees: good, fair, and bad. The evaluation result

Fig. 2 Implementation flow chart of intelligent lighting control method

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should be an integrated visual assessment of each image. When performing the evaluation, the subjects need to consider the following factors: the image definition, the image color, and the image noise. Obviously, many factors will affect the imaging lighting effect, such as the observation distance or the reflection character of interested target. Finally, after the ergonomic experiment, three image datasets with different subjective IQEDs will be built. Four objective IQED metrics are computed in this paper to describe the imaging effect of accumulated image datasets in quantification. They are the image region contrast, the image edge blur, the image gray deviation, and the image noise. The image region contrast represents the intensity difference among different image regions. The image edge blur means the edge spreading degree of image boundaries among different image regions. The image gray deviation is the intensity deviation degree between the original material color and its degenerated image color. The image noise reflects the contaminated degree of some unwanted information in image. Obviously, three image datasets will be used to generate the objective IQEDs datasets. Then, for each image dataset, four objective IQED datasets will be gotten. The k-means is used to analyze the distribution threshold of these datasets above. The k-means method is a kind of cluster technique which uses the iteration computation rule to realize the data partition [8]. In this paper for the sake of simpleness, it is supposed that each IQED dataset only has one cluster center. After the distribution estimation, 12 cluster centers can be calculated. Obviously, because the objective IQED datasets are built by the ergonomic method, the computed objective IQED metrics encapsulate the visual characters of system user. They can be regarded as the benchmark for the following computation.

3.3

The Online Stage

After the offline stage, the distribution thresholds of objective IQED metrics can be computed; then, they can be used for the lighting control. In the online stage, when this system works, first the camera collects one image from the scene and its objective IQED metrics will be computed. Then, the distance of each IQED metric between the cluster center gotten in the offline stage and the value computed in this stage will be calculated; e.g., they can be computed by (1) to (4). Finally, a decision function will be used to assess the lighting effect of that image. A linear weighted method in (5) is computed. It is defined to decrease the computation complexity of lighting system; after all, we have four IQED variables, while the decision function only has one output variable FDecision. DICR ¼ jCMICR  MICR j

ð1Þ

DIEB ¼ jCMIEB  MIEB j

ð2Þ

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DIGD ¼ jCMIGD  MIGD j

ð3Þ

DIN ¼ jCMIN  MIN j

ð4Þ

FDecision ¼ x0  DICR þ x1  DIEB þ x2  DIGD þ x3  DIN

ð5Þ

where symbols CMICR, CMIEB, CMIGD, and CMIN are the cluster centers of the objective IQED metrics captured in the offline stage; symbols MICR, MIEB, MIGD, and MIN are the objective IQED metrics captured in the online stage; x0, x1, x2, and x3 are weights, here x0 = 0.25, x1 = 0.15, x2 = 0.35, and x3 = 0.25. A kind of optimal lighting control method which is named as the “best from all (BFA)” is employed in this paper. As we have stated in Sect. 2, four streetlights are installed in the corner of intersection and each of them can implement the lighting output with three intensity degrees. Thus, we can have 3  3  3  3 = 81 different lighting effect outputs in that application. When carrying out the optimal lighting control, first eighty-one typical lighting outputs above will be implemented traversely and then the corresponding images of each lighting control method will be recorded. Second, the objective IQED metrics will be computed for each image and the lighting effect evaluation will be made by Eq. (5). Finally, this system will select only one lighting intensity output which has the smallest value of FDecision as the final control method of the LED lighting system.

4 Experiments and Discussions To test the validity of the proposed method, an experimental system is built. The simulation program of this system is written by C code in our PC (2.4 GHz CPU and 3 GB RAM).

4.1

The Experimental System and Data

Figure 3 shows the experimental system and the image data of the intelligent lighting application which are designed for the dark field surveillance test. In Fig. 3, (a) is the photograph of the lighting experimental system; (b), (c), and (d) are the

Fig. 3 Experiment system and the corresponding image data

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images captured by this system which have one vehicle model in the scenes. The lighting intensities in (b), (c), and (d) are strong, normal, and weak, respectively. In this experimental system, to test the validity of the proposed method, four LED lamps and one CCD camera are utilized. To imitate the practical situation in the intersection, four LED lamps are placed in the corner of a rectangle region; the size of that region is 50 cm  50 cm; and the CCD camera is placed just behind one LED lamp. Regarding the lighting lamp, each LED surface source has nine bulbs. Their intensity output degree is 3.

4.2

The Results of Ergonomic Experiment

A kind of subjective image quality evaluation software in [9] is used here. Figure 4 shows the experimental data samples. When this software works, first it plays image data in the screen for 5 s; then, the subjects can give score for the displayed image according to their subjective cognition results. The maximum evaluation degree is 3. A series of typical image data are displayed: A vehicle model is placed in different places of the rectangle range; the attitudes of vehicle are varied; and the LED lamps are set with different intensity outputs. Eight subjects participate in this experiment. They are male; their ages are from 21 to 37; and their uncorrected eyesight is better than 0.8. After a primary training, they are asked to perform the formal experiment. This experiment is performed in a darkroom; a liquid crystal display is used to display image data. The image data size is large than 600.

4.3

The Computation Results of Objective IQED Metrics

The objective IQED metrics are used to analyze the lighting effect of image dataset created from the ergonomic experiment. Table 1 shows the threshold distribution experimental results of the corresponding image datasets. Four metrics are computed here. In Table 1, the minima, the maxima, and the cluster centers of the

Fig. 4 Experiment data samples

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Index

MICR

MIEB

MIGD

MIN

Minimum Maximum Cluster center

0.2134 0.8346 0.4768

1.2745 8.0438 4.3721

0.3846 0.4237 0.3987

0.0021 1.0040 0.0035

threshold computation results are given. From Table 1, it can be seen that the cluster center can be estimated by the k-means method since only one cluster center is considered here. Currently, although the experimental data is limited, however, the perception results of subjects will be convergent with the accumulation of experimental data from the statistics point of view. After a preliminary analysis, the cluster center can be regarded as the ground truth for the lighting effect evaluation.

4.4

The Experimental Results of Intelligent Lighting Control

To test the validity of the proposed method, first a vehicle model is put in the experimental system and an initial lighting is given. Here, the initial lighting means all the LED lamps implement the highest intensity outputs. Second, this system performs the intelligent lighting control and the corresponding images are recorded. Third, the subjects are asked to evaluate the lighting effect of the recorded images before and after the applications of the proposed method. Figure 5 shows some results of the proposed lighting control method. In Fig. 5a and c are the original images which do not perform any intelligent controls, while (b) and (d) are the images which implement the intelligent lighting control. Obviously, the visual output effects of (b) and (d) are better than the effects of (a) and (c). Other experimental results also indicate that all the subjects think that the lighting effects can be improved distinctly after the use of the proposed intelligent control method.

Fig. 5 Experiment result samples of the intelligent lighting control

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5 Conclusion A kind of intelligent lighting control method for the dark field surveillance is proposed. Before this system is employed, first, the typical image datasets are accumulated and the ergonomic experiment is used to classify these datasets above according to the subjective lighting effect evaluation degrees. Second, four objective IQED metrics are used to compute the quantified indexes of these image datasets above. Third, the k-means is used to analyze the distribution thresholds of objective IQED metrics. Finally, when this system works, it will compute the IQED metrics for a captured image and compare its IQED results with the distribution thresholds of IQED metrics above, and then, a kind of optimal lighting control can be made. Some experiments have indicated the validity of the proposed method. Acknowledgements This work is supported by the National Nature Science Foundation of China under Grant No. 61501016 and the open project of the State Key Laboratory of Intense Pulsed Radiation Simulation and Effect under Grant No. SKLIPR1713. Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of University of Science and Technology Beijing. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection.

References 1. Nazare AC Jr, Schwartz WR (2016) A scalable and flexible framework for smart video surveillance. Comput Vis Image Und 144:258–275 2. Mabrouk AB, Zagrouba E (2018) Abnormal behavior recognition for intelligent video surveillance systems: a review. Expert Syst Appl 91:480–491 3. Hassan Y, Orabi M, Ismeil M et al (2017) Study the effect of series and parallel LEDs connections on the output current ripple for LED driver of solar street lighting. In: IMESC, pp 1492–1499 4. Ran L, Zhang X, Zhao C et al (2013) Preliminary exploration on visual ergonomics in LED illumination and national standard system framework for visual ergonomics. In: CIFSSL, pp 198–201 5. Liu H, Lu H, Zhang Y (2017) Image enhancement for outdoor long-range surveillance using IQ-learning multiscale Retinex. IET Image Process 11:786–795 6. Lee H, Jung S, Kim M et al (2017) Synthetic minority over-sampling technique based on fuzzy K-means clustering for imbalanced data. In: ICFTA, pp 1–6 7. Liu H, Zhou Q, Yang J et al (2017) Intelligent luminance control of lighting systems based on imaging sensor feedback. Sensors 17: 321-1–321-24 8. Saxena A, Prasad M, Gupta A et al (2017) A review of clustering techniques and developments. Neurocomputing 267:664–681 9. Liu H, Yan B, Lv M et al (2017) Computer-aided visual function assessment using subjective image quality evaluation metrics. In: ICMMESE, pp 57–65

Investigating the Comfort Distance of Chinese in Eight Directions Xiaoqing Yu and Yu-Chi Lee

Abstract The aim of the study was to investigate the preferred comfort distance that Chinese people keep between themselves and others. An experiment was carried out to measure the comfort distance around participants, and the gender effect of the participant was evaluated. Twenty-eight participants (15 females) were recruited in the experiment. All the participants were asked to stand naturally when a confederate approaching them. The comfort distances between participants and confederates in the eight directions (0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°) were collected to analyze. The results indicated that the comfort distance in the front was larger than that in the lateral and rear. In addition, there was no significant difference between male and female participants on the comfort distance under the selected eight directions. The study could contribute to the research on the social interactions of Chinese. Keywords Comfort distance


Directions
Chinese
Gender effect

1 Introduction In the social psychological aspect, the ‘personal distance’ is defined as the emotionally tinged zone around the human body that people feel like ‘their own space’. This distance cannot be intruded by others without arousing discomfort situations [1–3]. People tend to take a larger distance to spatial violations in uncomfortable conditions than in comfortable situations [4, 5]. The typical method of measuring the personal distance is based on the judgment of comfort distance; that is, the participants have to stop the confederate approaching at the point where they are still comfortable but about to be uncomfortable [6, 7]. Based on the results of previous studies, the comfort distance was influenced by many factors such as culture, participant’s gender, and age [8–10]. Baldassare and X. Yu
Y.-C. Lee (&) School of Design, South China University of Technology, Guangzhou 510641, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_53

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Feller compared the comfort distance between native and foreign students in the USA [11]. Ford and Graves stated that Mediterranean population maintained a closer distance than the Northern European and Northern American population [12]. The preferred comfort distance in Asian societies was evaluated by Sorokowska et al. [13]. The study collected the comfort distances from 59 countries, including China, by using a questionnaire. Participants were asked to imagine themselves as the person on the graph and to determine the comfort distance. In addition, most studies conducted the ‘stop-distance’ experiment only considering the comfort distance in the front [6, 14]. Several researches discussed the distance in the lateral and rear of the participants [15, 16]. In immersive virtual reality, Bailenson et al. found that participants kept a longer distance when they were in front of the agent than behind the agent [17]. However, there was little in-depth research on the comfort distance of Chinese under the real situation. Furthermore, the information of preferred comfort distances in the eight directions (0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°) around Chinese is still lacking. Hence, the present study aimed to measure the eight directions of comfort distances of Chinese participants under the real situation. In addition, the differences in the perception of comfort distance between male and female participants were evaluated.

2 Method 2.1

Participants

Twenty-eight university students (15 women) aged from 18 to 36 years (Average = 21.1, SD = 3.7) were recruited through advertising. All participants had normal or corrected-to-normal vision. They had no prior knowledge about the scientific purpose of the experiment. A written consent was provided for the participants before the experiment.

2.2

Setting and Confederates

The experiment was conducted in the laboratory with 4  8  4 m3 space. There was a marked point on the ground, and the center of the participants’ feet stepped separately on the point. Eight straight yellow lines were attached from the point to the eight directions. The eight angles, ranging from 0° to 360° and spaced 45° apart, were set up for evaluation. The experiment setting was illustrated in Fig. 1. Two confederates, a male and a female with normal appearance, were selected in the experiment. Both of the confederates were unknown to all the participants. They wore the same suit of casual clothes through the whole experiment. During each trial, the confederate walked toward the participants at a constant speed with arms naturally swung (see in Fig. 2).

Investigating the Comfort Distance of Chinese in Eight Directions

Fig. 1 Eight directions around the participants

Fig. 2 Scene when the confederate was approaching

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Procedure

All participants received a written experiment instruction, and the experimenter presented the purpose of the task orally. Before the experiment, the participants were required to practice for becoming familiar with the whole procedure. In the first part, the participant stood on the center point and gazed ahead with arms naturally dropping. The initial distance between the confederate and the participant was 3 m. Either the male or the female confederate walked toward the participants from one of the eight directions at a speed of 0.5 m/s. The participants were asked to say ‘stop’ when they still felt comfortable but were about to feel uncomfortable. The confederate stopped and stood on the position where the participants called stop. The participant had a chance to adjust the position of confederate slightly to reconfirm the comfort distance due to inertia after the participant said stop. The chest-to-chest distance between participant and confederate was measured by a digital laser distance measurer (JM-G25240, JIMIHOME, Shanghai, China). The precision of the device was 2 mm. The trial was repeated three times in every eight directions. In the second part, the other confederate attended the experiment following the same procedure of the first part. Each participant had a 5 min break between the two parts and responded to a total of 48 trials in the whole procedure. Besides, the order of the eight directions was randomized assigned. The digital laser distance measurer was calibrated before each participant’s experiment.

2.4

Statistical Analysis

In the study, the data were analyzed by SPSS 19.0 with a significance level at 0.05. The two-way ANOVA was used to clarify the relationship between the independent variables (direction and gender) and the measurements (comfort distance). For further analyzing the effects of direction on comfort distance, one-way ANOVA was performed. Moreover, Duncan’s multiple range test (MRT) was applied for post hoc multiple comparisons. A t-test was conducted to evaluate the participant’s gender effect on comfort distance in the eight directions.

3 Results The two-way ANOVA results found non-significant effect of participant’s gender and non-significant interaction term that can be shown in Table 1. Additionally, the results revealed a significant effect on the direction (p < 0.001). Table 2 shows the means (standard deviations) of comfort distance of all the participants in the eight directions. The results of the one-way ANOVA showed that the direction had a significant effect on the comfort distance (p < 0.001). The

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Table 1 Results of two-way ANOVA Terms

F

df

p-value

Direction Participant’s gender Direction  participant’s gender

19.041 0.000 0.453

7 1 7

0.000 0.926 0.868

Table 2 Means (standard deviations) of comfort distance (cm) of eight directions and the Duncan’s MRT results (N = 28) Directions

0°

45°

90°

135°

180°

225°

270°

315°

Distance

74.1 (15.2) A

66.7 (12.6) B

62.4 (13.1) B

45.8 (11.0) C

45.0 (13.8) C

48.6 (11.6) C

62.5 (12.8) B

63.9 (13.1) B

Group

largest comfort distance was 74.1 cm when the confederate was in front of the participants. The closest comfort distance was found in the direction of 180° (rear side: 45.0 cm). Moreover, in the post hoc multiple comparisons, the results showed that the comfort distances in the eight directions were divided into three groups. The group A was the distance in the 0° (front side) which was larger than the other seven directions (p < 0.05). The group B was the lateral comfort distances in the four directions (45°, 90°, 270°, 315°). The other three distances in the rear areas (135°, 180°, 225°) of the participants were classified to the group C. Figure 3 illustrates the means of the comfort distance around the participants when they were approached from the eight directions. The distance in the front side of the participant was larger than that in the rear areas. The comfort distance in the left and right side of the participants was similar. Table 3 shows the means (standard deviations) of comfort distance of the male and the female participants. The independent t-test results under each direction between male and female participants were also demonstrated in Table 3. No significant difference was found in the preferred comfort distance between male and female participants in the selected eight directions.

4 Discussion The results of this study indicated that the mean of comfort distance in front of the participants was 74.1 cm, which accorded with the definition of the personal distance [1]. The distance in the front was larger than that in the lateral and rear. The possible reason to explain the finding was the participants felt greater threat and pressure when they were approached directly in the front with eye contact. Amaoka et al. established the mathematical model of comfort distance in the virtual reality and indicated that the comfort distance in the lateral and rear was half of that in the

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Fig. 3 Comfort distance (cm) around the Chinese participants when they were approached from eight directions

Table 3 Means (standard deviations) of comfort distance (cm) of male and female participants and the results of independent t-test Directions

0°

45°

90°

135°

180°

225°

270°

315°

Male (N = 13) Female (N = 15) p-value

71.4 (10.7) 76.5 (18.3) 0.37

66.6 (11.5) 66.7 (13.9) 0.97

64.2 (11.4) 60.9 (14.6) 0.52

47.0 (9.8) 44.8 (12.2) 0.61

43.0 (8.8) 46.7 (17.1) 0.47

48.2 (8.3) 48.9 (14.2) 0.87

64.8 (12.9) 60.4 (12.7) 0.37

63.1 (12.0) 64.5 (13.1) 0.76

front (76.3 cm), regardless of the gender effect [16]. The results in this study reported that the front comfort distance of Chinese was 74.1 cm, which was similar with the findings of Amaoka et al. [16]. Besides, the distance in the lateral and rear was 0.86 times and 0.6 times that in the front, respectively. Participants stated that they were insecure when they could not see the confederate approaching them in the lateral and rear side. Hence, the comfort distance in the lateral and the rear in the real situation was relatively larger than the previous research results in virtual reality. Iachini et al. suggested that the preferred distance in front of participants was not affected by the participants’ gender in the real environment, which was also found in the present study [18]. Besides, non-significant differences in the comfort distance were found between the genders of the participant in the selected eight

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directions. As a result, there was no difference in the perception of comfort distance between the male and the female when they were approached so that they maintain a similar size of safety buffer zone to avoid the invasion of others. The comfort distance has been discussed by researchers for decades. There is still little information on the comfort distance of Chinese in real situation. The present study evaluated the gender effect on the eight directions (0°, 45°, 90°, 135°, 180°, 225°, 270°, 315°) and the comfort distance around Chinese people was illustrated. The findings of this study provided useful information for social interaction of Chinese in various situations. In future research, the number of the participants will be expanded and more factors such as age and body shape will be considered.

5 Compliance with Ethical Standards The study was approved by the Logistics Department for Civilian Ethics Committee of South China University of Technology. All subjects who participated in the experiment were provided with and signed an informed consent form. All relevant ethical safeguards have been met with regard to subject protection. Acknowledgements The authors would like to express our great appreciation to the financial support by the South China University of Technology under the grant No. D6192270.

References 1. Hall ET (1966) The hidden dimension. Doubleday, New York 2. Hayduk LA (1983) Personal space: where we now stand. Psychol Bull 94:293–335 3. Gifford R, Sacilotto PA (1993) Social isolation and personal space: a field study. Can J Behav Sci 25:165–174 4. Dosey MA, Meisels M (1969) Personal space and self-protection. J Pers Soc Psychol 11:93– 97 5. Kennedy DP, Gläscher J, Tyszka JM et al (2009) Personal space regulation by the human amygdala. Nat Neurosci 12:1226–1227 6. Gessaroli E, Santelli E, di Pellegrino G et al (2013) Personal space regulation in childhood autism spectrum disorders. PLoS ONE 8:e74959 7. Iachini T, Coello Y, Frassinetti F et al (2014) Body space in social interactions: a comparison of reaching and comfort distance in immersive virtual reality. PLoS ONE 9:e111511 8. Remland MS, Jones TS, Brinkman H (1995) Interpersonal distance, body orientation, and touch: effects of culture, gender, and age. J Soc Psychol 135:281–297 9. Uzzell D, Horne N (2006) The influence of biological sex, sexuality and gender role on interpersonal distance. Br J Soc Psychol 45:579–597 10. Sussman NM, Rosenfeld HM (1982) Influence of culture, language, and sex on conversational distance. J Pers Soc Psychol 42:66–74 11. Baldassare M, Feller S (1975) Cultural variations in personal space. Ethos 3:481–503

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12. Ford JG, Graves JR (1977) Differences between Mexican-American and White children in interpersonal distance and social touching. Percept Mot Skills 45:779–785 13. Sorokowska A, Sorokowski P, Hilpert P et al (2017) Preferred interpersonal distances: a global comparison. J Cross Cult Psychol 48:577–592 14. Ruggiero G, Frassinetti F, Coello Y et al (2017) The effect of facial expressions on peripersonal and interpersonal spaces. Psychol Res 81:1232–1240 15. Hayduk LA (1981) The shape of personal space: an experimental investigation. Can J Behav Sci 13:87–93 16. Amaoka T, Laga H, Nakajima M (2009) Modeling the personal space of virtual agents for behavior simulation. In: 2009 international conference on CyberWorlds. IEEE, pp 364–370 17. Bailenson JN, Blascovich J, Beall AC et al (2003) Interpersonal distance in immersive virtual environments. Pers Soc Psychol Bull 29:819–833 18. Iachini T, Coello Y, Frassinetti F et al (2016) Peripersonal and interpersonal space in virtual and real environments: effects of gender and age. J Environ Psychol 45:154–164

Design and Application of a Ventilation System in a Washing Board Room Based on Numerical Simulation Bin Yang, Jianwu Chen, Shasha Liang, Shulin Zhou, Yanqiu Sun and Yunmeng Li

Abstract This paper takes one electronics industry washing board room as the research object and designs a push–pull ventilation system as the protection measures of the washing board room. Using the simulation method, this paper studies the influence of the ratio of supply and discharge air volume (k) on the push–pull ventilation system and the protective effect of toluene. It is found that the protective effect is best when the k value was 2.5. The ventilation system after on-site reform, of which test results of wind speed and poison concentration are consistent with the simulation results, can effectively protect the health of workers.




Keywords Uniform flow Push–pull ventilation Ventilation and protection technology


Washing board room


1 Purpose Field investigation and study found that it is easy to disturb the airflow in the process of washing boards, and the effect of the local ventilation facilities is so poor that affect workers’ work [1, 2]. Due to the above reasons, washing plate room is more suitable to use horizontal uniform airflow push–pull ventilation system [3, 4]. So, this paper chooses a plate-washing room as the research object which adopts a uniform airflow push–pull ventilation system [5–7], to establish a mathematical model of blowing-suction ventilation. And using the method of simulation [8], the effect of k value on the blowing ventilation system between washing plates and the protective effect of toluene are further studied. It has great significance to protect the toxicants in the washing process of electronics industry.

B. Yang (&)
J. Chen
S. Liang
S. Zhou
Y. Sun China Academy of Safety Science and Technology, Beijing 100029, China e-mail: [email protected] Y. Li Beijing Institute of Petrochemical Technology, Beijing 102617, China © Springer Nature Singapore Pte Ltd. 2020 S. Long and B. S. Dhillon (eds.), Man–Machine–Environment System Engineering, Lecture Notes in Electrical Engineering 576, https://doi.org/10.1007/978-981-13-8779-1_54

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2 Methods 2.1

The Design of Blowing-Suction Ventilation System in a Washing Board Room

The length, width, and height of the working space of the washing board room are, respectively, 2.5, 1.5, and 2.5 m, and the length and width of the workpiece are both 0.8 m. A 0.95-m-long and 0.95-m-wide parallel-flow square air supply hood and exhaust hood was designed as the research object, because the width of the air supply hood and the exhaust hood need to be larger than the size of the workpiece. Reference to the size of the printing floor and washing plate room, the table size is set to 3.5 m long  0.95 m wide. This paper establishes a blowing-suction ventilation system calculation model of a washing plate room as shown in Fig. 1.

2.2

Setting of Parameters for Numerical Simulation

According to the actual situation of the washboard operation and the relevant measured data, combined with the fluent numerical simulation method and the established mathematical model [9, 10], the relevant parameters of ventilation system in the process of the washboard operation are determined. Solution parameters and boundary condition settings are shown in Table 1.

Fig. 1 Geometric of Poison hazard protection ventilation system

Design and Application of a Ventilation System … Table 1 Parameter setting of boundary conditions and solve

2.3

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Boundary conditions

Define

Solver Viscous model Species model Reactions volumetric Mixture-template Energy Inlet boundary type Inlet velocity magnitude Hydraulic diameter Turbulence intensity Outlet boundary type

Segregated k-epsilon Species transport off C7H8-air mixture-template On Velocity inlet 0.5 m/s 0.95 m 4.46% Velocity inlet

Effect of K Value on Distribution of Poison Concentration

This paper simulates and analyzes the airflow organization and poison control in the washing plate room when k takes different values (1.5, 2.2, 2.3, 2.5, 2.7, 3). When K takes different values, the concentration distribution of toluene component in the center of worktable is shown in Fig. 2. When k = 1.5, the toluene escapes from both sides of the workbench. Due to the far supply air control distance, the part of the supply airflow blows from both sides of exhaust hood and forms a small vortex above the exhaust hood. In addition, because the density of vapor phase toluene is larger than the air, the toluene gas settles under the action of its own gravity that most of toluene gas accumulates at the bottom of the space and a small part of toluene gas continuously moves to the upper part of the space under the airflow and diffusion. When k = 2.2 and 2.3, a small part of the airflow blown out from both sides of the exhaust hood, at the same time, a small part of the toluene gas escapes and settles to the bottom of the working platform which deposits and diffuses in the air over time. When k = 2.5, a very small amount of toluene gas still can escape from both sides of the stage and diffuse to the lower part while the workbench has a trace of toluene pollutants in the lower part at k = 2.7. When k = 3, the exhaust effect is so strong that toluene gas is basically inhaled and discharged by exhaust hood, and there is no toluene pollutant around the bench escape. When k takes different values, the toluene mass concentration curve of human respiratory band position is shown in Fig. 3. It can be seen from Fig. 3 that when k = 1.5, the mass concentration of toluene on the height of respiratory band and on the edge of the working table is obviously larger, while at k = 2.2 and 2.3, the mass concentration of toluene is still above the standard and the highest concentration of respiratory band exceeds 100 mg/m3. With the increase of k value, the mass concentration of toluene decreases gradually.

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Fig. 2 Concentration magnitude of different k values

Fig. 3 Concentration profile of toluene in different k

When k  2.5, it is well controlled the mass concentration of toluene and when k = 2.5, the maximum concentration of toluene was 19.6 mg/m3, while the concentration of toluene along the respiratory zone was very low. When k = 2.7 and 3, the mass fraction of toluene is almost zero, and the protective effect is the best. From a comprehensive economic point of view, it can satisfy the purpose of controlling toluene pollution source when k = 2.5.

Design and Application of a Ventilation System …

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3 Application 3.1

Ventilation System After On-Site Reform

For a push–pull ventilation system, the air velocity of blowing hood set to 0.5 m/s, so that the air supply reaches to 1620 m3/h. Through the simulation calculation, it is the best effect on controlling the harmful gas generated by the panel washing operation when the air volume of the blowing hood is 2.5 times of the suction hood. Therefore, wind speed of air blowing hood should be 1.25 m/s, and air exhaust volume is 4050 m3/h. The pipe of the exhaust system is numbered as shown in Fig. 4, while the length of the pipe and exhaust volume are marked. According to the air volume of each pipe section and the selected flow rate, the section size and unit length frictional resistance of each pipe section on the most adverse loop are determined. According to the design manual [11–13], the frictional resistance and the partial resistance along the pipelines are calculated, and the total system resistance is 943.9 Pa. Therefore, fan air volume should be 4657.5 m3/h, fan discharge pressure should be 1085.5 Pa.

3.2

System Speed Detection After On-Site Reform

The ventilation system uses high-efficiency filter device to achieve uniform air supply, using uniform grille uniform exhaust to meet the airflow uniformity. The results of wind speed test are shown in Table 2. Table 1 shows that when the k of ventilation system is about 2.5, the table control surface wind speed of poison hazard protection ventilation system in a washing board room is satisfied to the standards of uniform airflow push–pull ventilation system, and the wind speed unevenness of the system is significantly reduced.

Fig. 4 Exhaust system

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Table 2 Results of wind speed test Average

Test results (m/s)

(Max, Min)

Judgment result (