Qr code
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
Click: times

Open time:..

The Last Update Time:..

Using Body-Worn Sensors for Preliminary Rehabilitation Assessment in Stroke Victims With Gait Impairment

Hits : Praise

Indexed by:期刊论文

Date of Publication:2018-01-01

Journal:IEEE ACCESS

Included Journals:SCIE

Volume:6

Page Number:31249-31258

ISSN No.:2169-3536

Key Words:Body-worn sensors; rehabilitation assessment; precision medicine; stroke victims; gait impairment

Abstract:Improving health is an important driving factor of sensor technology applications. To meet the demands of precision medicine for medical rehabilitation and elderly guardianship, using wearable sensors to get kinematics, kinetics, and biochemical information has become an interdisciplinary research hotspot recently. This paper proposed a low-cost, intelligent, and lightweight wearable platform for rehabilitation assessment in stroke victims with gait impairment. The paper starts from the sensor physical properties and human physiology structure, and aims to solve sensor drift problem by zero velocity update algorithm. A complementary filter based on proportional integral controller was adopted to eliminate computational errors. Preliminary clinical gait experiments results showed that the protocol we have designed according to the proposed guidelines had demonstrated to be operatively simple and efficient compared with existing methods. The expectation of this case study is to develop a dedicated tool for supporting diagnosis and rehabilitation in the hospital.