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Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training

Wenjun Ye, Zhijun Li, Chenguang Yang, Fei Chen, Chun-Yi Su

International Journal of Humanoid Robotics, Start page: 1650031

Swansea University Author: Chenguang Yang

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DOI (Published version): 10.1142/S0219843616500316

Abstract

The paper studies the control design of an exoskeleton robot based on electromyography (EMG). An EMG-based motion detection method is proposed to trigger the rehabilitation assistance according to user intention. An adaptive control scheme that compensates for the exoskeleton's dynamics is empl...

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Published in: International Journal of Humanoid Robotics
ISSN: 0219-8436
Published: 2017
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URI: https://cronfa.swan.ac.uk/Record/cronfa30811
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first_indexed 2016-10-24T19:27:49Z
last_indexed 2018-04-13T19:11:20Z
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spelling 2018-04-13T15:27:10.4561001 v2 30811 2016-10-24 Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training d2a5024448bfac00a9b3890a8404380b Chenguang Yang Chenguang Yang true false 2016-10-24 EEN The paper studies the control design of an exoskeleton robot based on electromyography (EMG). An EMG-based motion detection method is proposed to trigger the rehabilitation assistance according to user intention. An adaptive control scheme that compensates for the exoskeleton's dynamics is employed, and it is able to provide assistance tailored to the human user, who is supposed to participate actively in the training process. The experiment results verify the effectiveness of the control method developed in this paper. Journal Article International Journal of Humanoid Robotics 1650031 0219-8436 Human-like learning control; EMG motion detection; SVM-based classification Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219843616500316 31 3 2017 2017-03-31 10.1142/S0219843616500316 COLLEGE NANME Engineering COLLEGE CODE EEN Swansea University 2018-04-13T15:27:10.4561001 2016-10-24T18:23:22.7799571 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Wenjun Ye 1 Zhijun Li 2 Chenguang Yang 3 Fei Chen 4 Chun-Yi Su 5 0030811-25102016104749.pdf ye2016.pdf 2016-10-25T10:47:49.0030000 Output 671755 application/pdf Accepted Manuscript true 2017-12-27T00:00:00.0000000 false
title Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training
spellingShingle Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training
Chenguang Yang
title_short Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training
title_full Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training
title_fullStr Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training
title_full_unstemmed Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training
title_sort Motion Detection Enhanced Control of an Upper Limb Exoskeleton Robot for Rehabilitation Training
author_id_str_mv d2a5024448bfac00a9b3890a8404380b
author_id_fullname_str_mv d2a5024448bfac00a9b3890a8404380b_***_Chenguang Yang
author Chenguang Yang
author2 Wenjun Ye
Zhijun Li
Chenguang Yang
Fei Chen
Chun-Yi Su
format Journal article
container_title International Journal of Humanoid Robotics
container_start_page 1650031
publishDate 2017
institution Swansea University
issn 0219-8436
doi_str_mv 10.1142/S0219843616500316
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description The paper studies the control design of an exoskeleton robot based on electromyography (EMG). An EMG-based motion detection method is proposed to trigger the rehabilitation assistance according to user intention. An adaptive control scheme that compensates for the exoskeleton's dynamics is employed, and it is able to provide assistance tailored to the human user, who is supposed to participate actively in the training process. The experiment results verify the effectiveness of the control method developed in this paper.
published_date 2017-03-31T03:37:33Z
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score 11.036706

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