IMU-based underwater sensing system for swimming stroke classification and motion analysis
2017 IEEE International Conference on Cyborg and Bionic Systems (CBS)(2017)
摘要
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.
更多查看译文
关键词
underwater sensing system,swimming stroke classification,underwater motion analysis,wearable sensing system,lower-limb movements,stroke-dependent quadratic discriminant analysis classifier,kinematics analysis,IMU-based wearable sensing system,swimming stroke recognition,time-domain feature selection
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要