TY - BOOK
T1 - Wearable systems based gait monitoring and analysis
AU - Gao, Shuo
AU - Chen, Junliang
AU - Dai, Yanning
AU - Hu, Boyi
N1 - Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. All rights reserved.
PY - 2022/3/16
Y1 - 2022/3/16
N2 - Wearable Systems Based Gait Monitoring and Analysis provides a thorough overview of wearable gait monitoring techniques and their use in health analysis. The text starts with an examination of the relationship between the human body's physical condition and gait, and then introduces and explains nine mainstream sensing mechanisms, including piezoresistive, resistive, capacitive, piezoelectric, inductive, optical, air pressure, EMG and IMU-based architectures. Gait sensor design considerations in terms of geometry and deployment are also introduced. Diverse processing algorithms for manipulating sensors outputs to transform raw data to understandable gait features are discussed. Furthermore, gait analysis-based health monitoring demonstrations are given at the end of this book, including both medical and occupational applications. The book will enable students of biomedical engineering, electrical engineering, signal processing, and ergonomics and practitioners to understand the medical and occupational applications of engineering-based gait analysis and falling injury prevention methods.
AB - Wearable Systems Based Gait Monitoring and Analysis provides a thorough overview of wearable gait monitoring techniques and their use in health analysis. The text starts with an examination of the relationship between the human body's physical condition and gait, and then introduces and explains nine mainstream sensing mechanisms, including piezoresistive, resistive, capacitive, piezoelectric, inductive, optical, air pressure, EMG and IMU-based architectures. Gait sensor design considerations in terms of geometry and deployment are also introduced. Diverse processing algorithms for manipulating sensors outputs to transform raw data to understandable gait features are discussed. Furthermore, gait analysis-based health monitoring demonstrations are given at the end of this book, including both medical and occupational applications. The book will enable students of biomedical engineering, electrical engineering, signal processing, and ergonomics and practitioners to understand the medical and occupational applications of engineering-based gait analysis and falling injury prevention methods.
KW - Ai based disease analysis
KW - Disease classification
KW - Falling injury prevention
KW - Gait features
KW - Gait monitoring and analysis
KW - Healthcare IoT
KW - Internet of medical things
KW - Motion detection
KW - Plantar stress distribution
KW - Rehabilitation training
KW - Wearable body signal sensing
UR - https://www.scopus.com/pages/publications/85159009416
U2 - 10.1007/978-3-030-97332-2
DO - 10.1007/978-3-030-97332-2
M3 - 书
AN - SCOPUS:85159009416
SN - 9783030973315
BT - Wearable systems based gait monitoring and analysis
PB - Springer International Publishing
ER -