IMU-based underwater sensing system for swimming stroke classification and motion analysis

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.