TY - GEN
T1 - Research of Gait Recognition Based on Human Electrostatic Signal
AU - Li, Mengxuan
AU - Chen, Xi
AU - Tian, Shanshan
AU - Wang, Yifei
AU - Li, Pengfei
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/20
Y1 - 2018/9/20
N2 - The electrostatic induction signal could be sensed when charged human body was walking, and discrepancy of walking habits such as gait frequency, stride of different individuals will be reflected in the signal. This paper proposed a method to recognize human gait by measuring electrostatic signal. A modified dynamic time warping algorithm was utilized to recognize human gait after de-noising the electrostatic signal which was acquired by a non-contact induction electrode. In order to verify the performance of this method, we collected 25 gait signal segments from 5 subjects, 5 signal segments for each subject. The result demonstrates that our method has a correct rate over 85%, and greatly shortens the operative time compared with the traditional DTW algorithm.
AB - The electrostatic induction signal could be sensed when charged human body was walking, and discrepancy of walking habits such as gait frequency, stride of different individuals will be reflected in the signal. This paper proposed a method to recognize human gait by measuring electrostatic signal. A modified dynamic time warping algorithm was utilized to recognize human gait after de-noising the electrostatic signal which was acquired by a non-contact induction electrode. In order to verify the performance of this method, we collected 25 gait signal segments from 5 subjects, 5 signal segments for each subject. The result demonstrates that our method has a correct rate over 85%, and greatly shortens the operative time compared with the traditional DTW algorithm.
KW - dynamic time warping
KW - electrostatic detection
KW - gait recognition
KW - gait signal
UR - http://www.scopus.com/inward/record.url?scp=85055677780&partnerID=8YFLogxK
U2 - 10.1109/IMCEC.2018.8469720
DO - 10.1109/IMCEC.2018.8469720
M3 - Conference contribution
AN - SCOPUS:85055677780
T3 - Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
SP - 1812
EP - 1817
BT - Proceedings of 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
A2 - Xu, Bing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018
Y2 - 25 May 2018 through 27 May 2018
ER -