Associate Professor
Supervisor of Master's Candidates
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Indexed by:会议论文
Date of Publication:2016-05-04
Included Journals:EI、CPCI-S、SCIE、Scopus
Page Number:647-652
Key Words:inertial measurement unit(IMU); phase detection; feature extraction; walking; swimming
Abstract:In this paper, a new method of human motion segmentation is proposed, which the inertial data of human movement was acquired through wearable Inertial measurement unit (IMU), and the feature of raw time series data was directly extracted, which was segmented by sliding window, and then by combining Support Vector Machines (SVM) classifier as the algorithm of motion phase detection. The experimental result shows that the potential pattern of human movement by segmenting the motion phase can be found through pattern recognition technique. The method can be applied into different human movements, such as walking and swimming. The feasibility and effectiveness has been verified.