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Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation

It is difficult for stroke patients with flaccid paralysis to receive passive rehabilitation training. Therefore, virtual rehabilitation technology that integrates the motor imagery brain-computer interface and virtual reality technology has been applied to the field of stroke rehabilitation and has...

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Autores principales: Xie, Ping, Wang, Zihao, Li, Zengyong, Wang, Ying, Wang, Nianwen, Liang, Zhenhu, Wang, Juan, Chen, Xiaoling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284764/
https://www.ncbi.nlm.nih.gov/pubmed/35847664
http://dx.doi.org/10.3389/fnagi.2022.892178
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author Xie, Ping
Wang, Zihao
Li, Zengyong
Wang, Ying
Wang, Nianwen
Liang, Zhenhu
Wang, Juan
Chen, Xiaoling
author_facet Xie, Ping
Wang, Zihao
Li, Zengyong
Wang, Ying
Wang, Nianwen
Liang, Zhenhu
Wang, Juan
Chen, Xiaoling
author_sort Xie, Ping
collection PubMed
description It is difficult for stroke patients with flaccid paralysis to receive passive rehabilitation training. Therefore, virtual rehabilitation technology that integrates the motor imagery brain-computer interface and virtual reality technology has been applied to the field of stroke rehabilitation and has evolved into a physical rehabilitation training method. This virtual rehabilitation technology can enhance the initiative and adaptability of patient rehabilitation. To maximize the deep activation of the subjects motor nerves and accelerate the remodeling mechanism of motor nerve function, this study designed a brain-computer interface rehabilitation training strategy using different virtual scenes, including static scenes, dynamic scenes, and VR scenes. Including static scenes, dynamic scenes, and VR scenes. We compared and analyzed the degree of neural activation and the recognition rate of motor imagery in stroke patients after motor imagery training using stimulation of different virtual scenes, The results show that under the three scenarios, The order of degree of neural activation and the recognition rate of motor imagery from high to low is: VR scenes, dynamic scenes, static scenes. This paper provided the research basis for a virtual rehabilitation strategy that could integrate the motor imagery brain-computer interface and virtual reality technology.
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spelling pubmed-92847642022-07-16 Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation Xie, Ping Wang, Zihao Li, Zengyong Wang, Ying Wang, Nianwen Liang, Zhenhu Wang, Juan Chen, Xiaoling Front Aging Neurosci Neuroscience It is difficult for stroke patients with flaccid paralysis to receive passive rehabilitation training. Therefore, virtual rehabilitation technology that integrates the motor imagery brain-computer interface and virtual reality technology has been applied to the field of stroke rehabilitation and has evolved into a physical rehabilitation training method. This virtual rehabilitation technology can enhance the initiative and adaptability of patient rehabilitation. To maximize the deep activation of the subjects motor nerves and accelerate the remodeling mechanism of motor nerve function, this study designed a brain-computer interface rehabilitation training strategy using different virtual scenes, including static scenes, dynamic scenes, and VR scenes. Including static scenes, dynamic scenes, and VR scenes. We compared and analyzed the degree of neural activation and the recognition rate of motor imagery in stroke patients after motor imagery training using stimulation of different virtual scenes, The results show that under the three scenarios, The order of degree of neural activation and the recognition rate of motor imagery from high to low is: VR scenes, dynamic scenes, static scenes. This paper provided the research basis for a virtual rehabilitation strategy that could integrate the motor imagery brain-computer interface and virtual reality technology. Frontiers Media S.A. 2022-06-30 /pmc/articles/PMC9284764/ /pubmed/35847664 http://dx.doi.org/10.3389/fnagi.2022.892178 Text en Copyright © 2022 Xie, Wang, Li, Wang, Wang, Liang, Wang and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Xie, Ping
Wang, Zihao
Li, Zengyong
Wang, Ying
Wang, Nianwen
Liang, Zhenhu
Wang, Juan
Chen, Xiaoling
Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation
title Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation
title_full Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation
title_fullStr Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation
title_full_unstemmed Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation
title_short Research on Rehabilitation Training Strategies Using Multimodal Virtual Scene Stimulation
title_sort research on rehabilitation training strategies using multimodal virtual scene stimulation
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284764/
https://www.ncbi.nlm.nih.gov/pubmed/35847664
http://dx.doi.org/10.3389/fnagi.2022.892178
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