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论文类型：会议论文

发表时间：2016-01-01

收录刊物：CPCI-S、SCIE

页面范围：644-649

关键字：wearable sensors; phase detection; motion measurement; machine learning; sport monitoring

摘要：This paper presents a monitoring system (CanoeSense) for canoe motion based on wearable Body Sensor Networks (BSNs). An effective motion segmentation method was applied to competitive sport, which can segment human motion phases automatically based on raw time series data that was acquired through wearable Inertial Measurement Units (IMUs). Orientation estimation algorithm was adopted to measure the attitude information of athletes' stroke motion of the canoe. By fusing the data of motion phases and attitude changes, the monitoring data may provide coach with a new performance monitoring method for improving coordination motions of two partners or adjusting the training plan in time. The experimental results showed that our system is able to simultaneously monitor motion phases and attitude changes of two athletes during training on the water.