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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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Quantitative assessment of dual gait analysis based on inertial sensors with body sensor network

Hits : Praise

Indexed by:期刊论文

Date of Publication:2013-01-01

Journal:SENSOR REVIEW

Included Journals:SCIE、EI、Scopus

Volume:33

Issue:1

Page Number:48-56

ISSN No.:0260-2288

Key Words:Motion; Limbs; Sensors; Human anatomy; Inertial; Gait; Human motion; Wireless; Data fusion

Abstract:Purpose - Due to the complex mechanism during walking, human gait takes plenty of information reflecting human motion. The method of quantitative measurement of gait makes a profound influence in many fields, such as clinical medicine, biped robot control strategy and so on. The purpose of this paper is to present a gait analysis system based on inertial measurement unit (IMU) and combined with body sensor network (BSN).
   Design/methodology/approach - The authors placed two wireless inertial nodes on the left and right ankles, so that the acceleration and angular velocity could be obtained from both sides at the same time. By using the kinematical model of the human gait, many methods such as time series analysis, pattern recognition and numerical analysis, are introduced to fuse the inertial data and estimate the sagittal gait parameters.
   Findings - The gait parameters evaluation gains a practical precision, especially in the gait phase detection and the process of how the two feet cooperate with each other has been analyzed to learn about the mechanism of biped walking.
   Research limitations/implications - The gait analysis procedure is off line, so that the system ensures sampling at a high rate.
   Originality/value - This gait analysis system can be utilized to measure quantitative gait parameters. Further, the coordination of dual gait pattern is presented. Last but not least, the system can also be put into capturing and analyzing the motion of other parts of the body.