EEG-modulated robotic rehabilitation system for upper extremity
This paper presents a novel electroencephalogram (EEG)-triggered upper extremity training system. Motor imagery EEG of upper extremity movements is adopted to trigger the Barrett WAM to perform rehabilitation training for patients with stroke. We focus on fully exploring the patient's movement...
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Taylor & Francis Group
2018-05-01
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Series: | Biotechnology & Biotechnological Equipment |
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Online Access: | http://dx.doi.org/10.1080/13102818.2018.1437569 |
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doaj-e4f762c21d524c54ade331e47508b67c2020-11-25T01:28:52ZengTaylor & Francis GroupBiotechnology & Biotechnological Equipment1310-28181314-35302018-05-0132379580310.1080/13102818.2018.14375691437569EEG-modulated robotic rehabilitation system for upper extremityBaoguo Xu0Aiguo Song1Guopu Zhao2Jia Liu3Guozheng Xu4Lizheng Pan5Renhuan Yang6Huijun Li7Jianwei Cui8Southeast UniversitySoutheast UniversityJiangsu Siming Engineering Machinery Co. Ltd.Nanjing University of Information Science & TechnologyNanjing University of Posts and TelecommunicationsChangzhou UniversityJinan UniversitySoutheast UniversitySoutheast UniversityThis paper presents a novel electroencephalogram (EEG)-triggered upper extremity training system. Motor imagery EEG of upper extremity movements is adopted to trigger the Barrett WAM to perform rehabilitation training for patients with stroke. We focus on fully exploring the patient's movement intention and attention from movement imagination EEG and controlling the WAM robot to perform training effectively. A position controller based on fuzzy logic is presented for the rehabilitation system to drive the WAM robot smoothly. Experimental results with seven participants are reported to show the feasibility and effectiveness of the robotic therapy system.http://dx.doi.org/10.1080/13102818.2018.1437569Neurorehabilitation robotstroke therapyfuzzy logicmotor imagery |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Baoguo Xu Aiguo Song Guopu Zhao Jia Liu Guozheng Xu Lizheng Pan Renhuan Yang Huijun Li Jianwei Cui |
spellingShingle |
Baoguo Xu Aiguo Song Guopu Zhao Jia Liu Guozheng Xu Lizheng Pan Renhuan Yang Huijun Li Jianwei Cui EEG-modulated robotic rehabilitation system for upper extremity Biotechnology & Biotechnological Equipment Neurorehabilitation robot stroke therapy fuzzy logic motor imagery |
author_facet |
Baoguo Xu Aiguo Song Guopu Zhao Jia Liu Guozheng Xu Lizheng Pan Renhuan Yang Huijun Li Jianwei Cui |
author_sort |
Baoguo Xu |
title |
EEG-modulated robotic rehabilitation system for upper extremity |
title_short |
EEG-modulated robotic rehabilitation system for upper extremity |
title_full |
EEG-modulated robotic rehabilitation system for upper extremity |
title_fullStr |
EEG-modulated robotic rehabilitation system for upper extremity |
title_full_unstemmed |
EEG-modulated robotic rehabilitation system for upper extremity |
title_sort |
eeg-modulated robotic rehabilitation system for upper extremity |
publisher |
Taylor & Francis Group |
series |
Biotechnology & Biotechnological Equipment |
issn |
1310-2818 1314-3530 |
publishDate |
2018-05-01 |
description |
This paper presents a novel electroencephalogram (EEG)-triggered upper extremity training system. Motor imagery EEG of upper extremity movements is adopted to trigger the Barrett WAM to perform rehabilitation training for patients with stroke. We focus on fully exploring the patient's movement intention and attention from movement imagination EEG and controlling the WAM robot to perform training effectively. A position controller based on fuzzy logic is presented for the rehabilitation system to drive the WAM robot smoothly. Experimental results with seven participants are reported to show the feasibility and effectiveness of the robotic therapy system. |
topic |
Neurorehabilitation robot stroke therapy fuzzy logic motor imagery |
url |
http://dx.doi.org/10.1080/13102818.2018.1437569 |
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