TY - GEN
T1 - IMU-based underwater sensing system for swimming stroke classification and motion analysis
AU - Zhang, Zhendong
AU - Xu, Dongfang
AU - Zhou, Zhihao
AU - Mai, Jingeng
AU - He, Zhongkai
AU - Wang, Qining
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - Swimming stroke classification and underwater motion analysis are important in swimming training. In this paper, we propose an IMU-based wearable sensing system for recognizing swimming strokes and motion analysis, focusing on lower-limb movements. The system measures 12 channels of posture signals from the shank, the thigh, and the foot of two legs. Three competitive swimmers were recruited in experiments. With a stroke-dependent quadratic discriminant analysis classifier and selected time-domain features, the proposed system can achieve a satisfactory classification accuracy of 98.63%±1.9%, 99.04%±0.91%, 99.10%±1.43%, 97.24%±1.71% for butterfly stroke, breaststroke, backstroke, front crawl, respectively. Besides, we carry out kinematics analysis of breaststroke. Preliminary results show that the IMU-based sensing system can be used for both swimming stroke classification and motion analysis.
AB - Swimming stroke classification and underwater motion analysis are important in swimming training. In this paper, we propose an IMU-based wearable sensing system for recognizing swimming strokes and motion analysis, focusing on lower-limb movements. The system measures 12 channels of posture signals from the shank, the thigh, and the foot of two legs. Three competitive swimmers were recruited in experiments. With a stroke-dependent quadratic discriminant analysis classifier and selected time-domain features, the proposed system can achieve a satisfactory classification accuracy of 98.63%±1.9%, 99.04%±0.91%, 99.10%±1.43%, 97.24%±1.71% for butterfly stroke, breaststroke, backstroke, front crawl, respectively. Besides, we carry out kinematics analysis of breaststroke. Preliminary results show that the IMU-based sensing system can be used for both swimming stroke classification and motion analysis.
UR - https://www.scopus.com/pages/publications/85050479906
U2 - 10.1109/CBS.2017.8266113
DO - 10.1109/CBS.2017.8266113
M3 - 会议稿件
AN - SCOPUS:85050479906
T3 - 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
SP - 268
EP - 272
BT - 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Cyborg and Bionic Systems, CBS 2017
Y2 - 17 October 2017 through 19 October 2017
ER -