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Title: Gait motion analysis based on WB-4 sensor with quaternion algorithm
Authors: Wang, Chunbao
Sun, Tongyang
Duan, Lihong
Liu, Quanquan
Lu, Zhijiang
Li, Meng
Chen, Pengfang
Wei, Chengdong
Hou, Anxin
Shen, Yajing
Liu, Qihong
Qin, Jian
Li, Weiguang
Shi, Qing
Wang, Yulong
Long, Jianjun
Wei, Jianjun
Zecca, Massimiliano
Wu, Zhengzhi
Keywords: Quaternions
Mathematical model
Robot sensing systems
Issue Date: 2016
Publisher: © IEEE
Citation: WANG, C. ... et al, 2016. Gait motion analysis based on WB-4 sensor with quaternion algorithm. Presented at the 6th Annual IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER 2016), Chengdu, China, 19th-22nd June 2016, pp. 279-283.
Abstract: Up to now, with the increasing of the elderly population, more and more patients are suffering from hemiplegia. The needs for hemiplegic rehabilitation is increasing quickly. As traditional rehabilitation, each patient must be treated by therapist, one by one. However, because of the different levels of therapists, the rehabilitation cannot be performed as the as the same. Normally, the rehabilitation status diagnosing is still be performed by therapists with the subjective experience. It caused the inhomogeneity on rehabilitation evaluation. It also sometimes causes negative influence on the rehabilitation effect. To solve these problems, many researches focusing on assessing the status of the hemiplegic patients quantitatively are proposed rehabilitation evaluation systems. Rehabilitation motion detection is the basis of the evaluation system, and it requires the participation of therapist. In this paper, a method is presented to detect lower limb motion of hemiplegic patients based on inertial sensor technology. The gesture quaternion of lower limb can be obtained through LPMS. With the matrix and Euler angle changing algorithm, combining with the simplified lower limb motion model, the rotation angle of joint can be computed. Finally, the curve of rotation angle of knee is established.
Description: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor: Research supported by Shenzhen Honkong Joint research Project (No.SGLH20150211093607169); Postdoctoral Science Foundation of China (No. 2015M580759); Technology Research Foundation of Basic Research Project of Shenzhen (JCYJ20150330102401102, JCYJ20150401171152771); Science and Technology Department of Guangdong(2014A020215004ˈ 2016A020220001); Guangxi Key Scientific and Technological Project (1598013-12).
Version: Accepted for publication
DOI: 10.1109/CYBER.2016.7574836
URI: https://dspace.lboro.ac.uk/2134/25947
Publisher Link: http://dx.doi.org/10.1109/CYBER.2016.7574836
ISBN: 9781509027323
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

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