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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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Body Sensor Network-Based Robust Gait Analysis: Toward Clinical and at Home Use

Hits : Praise

Indexed by:Journal Papers

Date of Publication:2019-10-01

Journal:IEEE SENSORS JOURNAL

Included Journals:SCIE

Volume:19

Issue:19,SI

Page Number:8393-8401

ISSN No.:1530-437X

Key Words:Body sensor network; gait analysis; magnetometric; calibration; inertial sensors; information fusion

Abstract:Gait analysis has become an important tool for diagnosing disease and evaluating disease progression. Currently gait analysis was mainly conducted by experienced physicians and relies on medical observation or complex medical equipment; hence, the application has been limited. This research aims to build an ambulatory gait analysis system based on the emerging body sensor networks. A calibration method for a magnetometer was proposed to deal with ubiquitous a magnetic disturbance. A proportional integral controller-based complementary filter and error correction of gait parameters have been defined with a multi-level data fusion algorithm. Preliminary gait analysis trials were conducted on both healthy subjects and patients with abnormal gait. Experimental results indicated that the proposed scheme has significant advantages in terms of test accuracy and efficiency, as well as operation complexity compared with conventional gait analysis approaches. Accordingly, measurement of gait abnormality may provide a wealth of information regarding neuromotor status and the characterization of some neurological disorders. It is concluded that the proposed gait analysis system has great potential as an auxiliary for medical rehabilitation.