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DALIAN UNIVERSITY OF TECHNOLOGY Login 中文
Wang Zhelong

Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates


Main positions:Professor, Head of Lab of Intelligent System
Other Post:自动化技术研究所所长
Gender:Male
Alma Mater:University of Durham
Degree:Doctoral Degree
School/Department:School of Control Science and Engineering
Discipline:Control Theory and Control Engineering. Pattern Recognition and Intelligence System. Detection Technology and Automation Device
Business Address:Lab of Intelligent System
http://lis.dlut.edu.cn/

Contact Information:0411-84709010 wangzl@dlut.edu.cn
E-Mail:wangzl@dlut.edu.cn
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GaitSense: A Potential Assistance for Physical Rehabilitation by Means of Wearable Sensors

Hits : Praise

Indexed by:会议论文

Date of Publication:2017-01-01

Included Journals:SCIE、EI、CPCI-S

Volume:1

Page Number:116-121

Key Words:Gait Analysis; Sensor Fusion; Physical Rehabilitation; Body sensor network; Wearable Devices

Abstract:Human walking contains important physiology, kinematic and dynamic information. There are many application prospect of human gait analysis in real life, such as monitoring the patient's recovery progress in clinical practice, the control strategy of bionic robot, etc. A wearable gait analysis platform (GaitSense) has been established based on wearable inertial/magnetic sensor and body sensor network. The platform can be used to collect acceleration, angular velocity and the geomagnetic signals in the process of walking movement. Accurate gait parameters can be calculated through sensor data fusion algorithm and error correction process. This paper aims to introduce the implement of the proposed GaitSense system for physical rehabilitation applications on the basis of summarizing the existing research content at home and abroad, taking account of the following issues: how to reduce the orientation estimation error and increase the accuracy of gait phases partition; how to analyze the symmetry between dual feet and the gait stability; how to eliminate the sensor misalignment and binding position deviation among multiple sensors. And the applicability of the widely used zero velocity update algorithm in the field of gait analysis. Clinical trials results demonstrated that the proposed GaitSense system has great potential as an assistance for physical rehabilitation.