TY  - BOOK
AU  - Gao,Shuo
AU  - Chen,Junliang
AU  - Dai,Yanning
AU  - Hu,Boyi
ED  - SpringerLink (Online service)
TI  - Wearable Systems Based Gait Monitoring and Analysis
SN  - 9783030973322
PY  - 2022///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Biomedical engineering
KW  - Biomechanics
KW  - Human-machine systems
KW  - Biomedical Engineering and Bioengineering
KW  - Biomechanical Analysis and Modeling
KW  - Medical and Health Technologies
KW  - Human-Machine Interfaces
KW  - Wearable Electronic Devices
KW  - Biosensing Techniques
KW  - Gait
N1  - Introduction -- Characteristics of Gait -- Wearable Gait Detection Technologies -- Gait Analysis Algorithms -- Medical Applications -- Occupational Applications. Conclusions
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. Provides students and practitioners with an overview of wearable gait monitoring techniques; Includes detailed insole sensor design considerations; Features engineering-based gait analysis methods
UR  - https://doi.org/10.1007/978-3-030-97332-2
ER  -