Indexed by:Conference Paper

Date of Publication:2019-01-01

Included Journals:CPCI-S、EI

Volume:2019-October

Page Number:3371-3376

Key Words:Swimming; inertial sensors; body sensor network; motion capture; posture recognition

Abstract:Swimming is a worldwide popular sports whose performance is highly correlated to the posture.To analyze and recognize the posture in swimming, a monitoring system (SwimSense) for human swimming training based on wearable inertial sensors is established. In this paper, one inertial sensor node is arranged on the surface of lumbar, and the raw sensor data concerning four swimming styles was collected. Through data fusion method and statistical analysis, the features of posture and statistical information were extracted. Subsequently, we proposed an action recognition method based on HMM. According to the classification results of different swimming strokes,it can be concluded that our method has high recognition accuracy and certain reference values, which can be used in swimming training in the future.