Sen Qiu
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Human Motion Phase Segmentation Based on Three New Features
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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.

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Associate Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates

Main positions:控制科学与工程学院副院长

Other Post:辽宁省药学会专委会副主委、大连市中西医结合学会医学人工智能专委会副主委、中国电子教育学会高等教育分会理事

Gender:Male

Alma Mater:大连理工大学

Degree:Doctoral Degree

School/Department:控制科学与工程学院

Discipline:Control Theory and Control Engineering

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