A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons
Herein, we propose a real-time stable control gait switching method for the exoskeleton rehabilitation robot. Exoskeleton rehabilitation robots have been extensively developed during the past decade and are able to offer valuable motor ability to paraplegics. However, achieving stable states of the...
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Frontiers Media S.A.
2021-04-01
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Series: | Frontiers in Neuroscience |
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Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2021.645374/full |
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Article |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Can Wang Can Wang Can Wang Ziming Guo Ziming Guo Ziming Guo Shengcai Duan Shengcai Duan Shengcai Duan Bailin He Bailin He Bailin He Ye Yuan Ye Yuan Ye Yuan Xinyu Wu Xinyu Wu Xinyu Wu Xinyu Wu Xinyu Wu |
spellingShingle |
Can Wang Can Wang Can Wang Ziming Guo Ziming Guo Ziming Guo Shengcai Duan Shengcai Duan Shengcai Duan Bailin He Bailin He Bailin He Ye Yuan Ye Yuan Ye Yuan Xinyu Wu Xinyu Wu Xinyu Wu Xinyu Wu Xinyu Wu A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons Frontiers in Neuroscience rehabilitation exoskeleton robot real-time motion stability gait switch surface electromyography motion intention recognition muscle fatigue |
author_facet |
Can Wang Can Wang Can Wang Ziming Guo Ziming Guo Ziming Guo Shengcai Duan Shengcai Duan Shengcai Duan Bailin He Bailin He Bailin He Ye Yuan Ye Yuan Ye Yuan Xinyu Wu Xinyu Wu Xinyu Wu Xinyu Wu Xinyu Wu |
author_sort |
Can Wang |
title |
A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons |
title_short |
A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons |
title_full |
A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons |
title_fullStr |
A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons |
title_full_unstemmed |
A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation Exoskeletons |
title_sort |
real-time stability control method through semg interface for lower extremity rehabilitation exoskeletons |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Neuroscience |
issn |
1662-453X |
publishDate |
2021-04-01 |
description |
Herein, we propose a real-time stable control gait switching method for the exoskeleton rehabilitation robot. Exoskeleton rehabilitation robots have been extensively developed during the past decade and are able to offer valuable motor ability to paraplegics. However, achieving stable states of the human-exoskeleton system while conserving wearer strength remains challenging. The constant switching of gaits during walking may affect the center of gravity, resulting in imbalance of human–exoskeleton system. In this study, it was determined that forming an equilateral triangle with two crutch-supporting points and a supporting leg has a positive impact on walking stability and ergonomic interaction. First, the gaits planning and stability analysis based on human kinematics model and zero moment point method for the lower limb exoskeleton are demonstrated. Second, a neural interface based on surface electromyography (sEMG), which realizes the intention recognition and muscle fatigue estimation, is constructed. Third, the stability of human–exoskeleton system and ergonomic effects are tested through different gaits with planned and unplanned gait switching strategy on the SIAT lower limb rehabilitation exoskeleton. The intention recognition based on long short-term memory (LSTM) model can achieve an accuracy of nearly 99%. The experimental results verified the feasibility and efficiency of the proposed gait switching method for enhancing stability and ergonomic effects of lower limb rehabilitation exoskeleton. |
topic |
rehabilitation exoskeleton robot real-time motion stability gait switch surface electromyography motion intention recognition muscle fatigue |
url |
https://www.frontiersin.org/articles/10.3389/fnins.2021.645374/full |
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doaj-13b3761af19a460282810b20721e1d152021-04-13T05:06:31ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2021-04-011510.3389/fnins.2021.645374645374A Real-Time Stability Control Method Through sEMG Interface for Lower Extremity Rehabilitation ExoskeletonsCan Wang0Can Wang1Can Wang2Ziming Guo3Ziming Guo4Ziming Guo5Shengcai Duan6Shengcai Duan7Shengcai Duan8Bailin He9Bailin He10Bailin He11Ye Yuan12Ye Yuan13Ye Yuan14Xinyu Wu15Xinyu Wu16Xinyu Wu17Xinyu Wu18Xinyu Wu19Guangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaShenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, ChinaCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Shenzhen, ChinaGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaShenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, ChinaCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Shenzhen, ChinaGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaShenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, ChinaCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Shenzhen, ChinaGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaShenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, ChinaCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Shenzhen, ChinaGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaShenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, ChinaCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Shenzhen, ChinaGuangdong Provincial Key Lab of Robotics and Intelligent System, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaShenzhen Institute of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen, ChinaCAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Shenzhen, ChinaGuangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, ChinaDepartment of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, Hong KongHerein, we propose a real-time stable control gait switching method for the exoskeleton rehabilitation robot. Exoskeleton rehabilitation robots have been extensively developed during the past decade and are able to offer valuable motor ability to paraplegics. However, achieving stable states of the human-exoskeleton system while conserving wearer strength remains challenging. The constant switching of gaits during walking may affect the center of gravity, resulting in imbalance of human–exoskeleton system. In this study, it was determined that forming an equilateral triangle with two crutch-supporting points and a supporting leg has a positive impact on walking stability and ergonomic interaction. First, the gaits planning and stability analysis based on human kinematics model and zero moment point method for the lower limb exoskeleton are demonstrated. Second, a neural interface based on surface electromyography (sEMG), which realizes the intention recognition and muscle fatigue estimation, is constructed. Third, the stability of human–exoskeleton system and ergonomic effects are tested through different gaits with planned and unplanned gait switching strategy on the SIAT lower limb rehabilitation exoskeleton. The intention recognition based on long short-term memory (LSTM) model can achieve an accuracy of nearly 99%. The experimental results verified the feasibility and efficiency of the proposed gait switching method for enhancing stability and ergonomic effects of lower limb rehabilitation exoskeleton.https://www.frontiersin.org/articles/10.3389/fnins.2021.645374/fullrehabilitation exoskeleton robotreal-time motion stabilitygait switchsurface electromyographymotion intention recognitionmuscle fatigue |