BCI-Based Rehabilitation on the Stroke in Sequela Stage
Background. Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and entered into the sequela stage of chronic stroke. Method. Studies...
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Wiley
2020-01-01
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Series: | Neural Plasticity |
Online Access: | http://dx.doi.org/10.1155/2020/8882764 |
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author | Yangyang Miao Shugeng Chen Xinru Zhang Jing Jin Ren Xu Ian Daly Jie Jia Xingyu Wang Andrzej Cichocki Tzyy-Ping Jung |
author_facet | Yangyang Miao Shugeng Chen Xinru Zhang Jing Jin Ren Xu Ian Daly Jie Jia Xingyu Wang Andrzej Cichocki Tzyy-Ping Jung |
author_sort | Yangyang Miao |
collection | DOAJ |
description | Background. Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and entered into the sequela stage of chronic stroke. Method. Studies have shown that motor imagery- (MI-) based brain-computer interface (BCI) has a positive effect on poststroke rehabilitation. This study used both virtual limbs and functional electrical stimulation (FES) as feedback to provide patients with a closed-loop sensorimotor integration for motor rehabilitation. An MI-based BCI system acquired, analyzed, and classified motor attempts from electroencephalogram (EEG) signals. The FES system would be activated if the BCI detected that the user was imagining wrist dorsiflexion on the instructed side of the body. Sixteen stroke patients in the sequela stage were randomly assigned to a BCI group and a control group. All of them participated in rehabilitation training for four weeks and were assessed by the Fugl-Meyer Assessment (FMA) of motor function. Results. The average improvement score of the BCI group was 3.5, which was higher than that of the control group (0.9). The active EEG patterns of the four patients in the BCI group whose FMA scores increased gradually became centralized and shifted to sensorimotor areas and premotor areas throughout the study. Conclusions. Study results showed evidence that patients in the BCI group achieved larger functional improvements than those in the control group and that the BCI-FES system is effective in restoring motor function to upper extremities in stroke patients. This study provides a more autonomous approach than traditional treatments used in stroke rehabilitation. |
format | Article |
id | doaj-art-ed0d60076d6a442caa9d7ab21f2ab0ce |
institution | Kabale University |
issn | 2090-5904 1687-5443 |
language | English |
publishDate | 2020-01-01 |
publisher | Wiley |
record_format | Article |
series | Neural Plasticity |
spelling | doaj-art-ed0d60076d6a442caa9d7ab21f2ab0ce2025-02-03T01:20:09ZengWileyNeural Plasticity2090-59041687-54432020-01-01202010.1155/2020/88827648882764BCI-Based Rehabilitation on the Stroke in Sequela StageYangyang Miao0Shugeng Chen1Xinru Zhang2Jing Jin3Ren Xu4Ian Daly5Jie Jia6Xingyu Wang7Andrzej Cichocki8Tzyy-Ping Jung9Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, ChinaDepartment of Rehabilitation, Huashan Hospital, Fudan University, Shanghai, ChinaKey Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, ChinaKey Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, ChinaGuger Technologies OG, AustriaBrain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex CO4 3SQ, UKDepartment of Rehabilitation, Huashan Hospital, Fudan University, Shanghai, ChinaKey Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, ChinaSkolkowo Institute of Science and Technology (SKOLTECH), 143026 Moscow, RussiaInstitute for Neural Computation and Institute of Engineering in Medicine, University of California San Diego, La Jolla, CA, USABackground. Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and entered into the sequela stage of chronic stroke. Method. Studies have shown that motor imagery- (MI-) based brain-computer interface (BCI) has a positive effect on poststroke rehabilitation. This study used both virtual limbs and functional electrical stimulation (FES) as feedback to provide patients with a closed-loop sensorimotor integration for motor rehabilitation. An MI-based BCI system acquired, analyzed, and classified motor attempts from electroencephalogram (EEG) signals. The FES system would be activated if the BCI detected that the user was imagining wrist dorsiflexion on the instructed side of the body. Sixteen stroke patients in the sequela stage were randomly assigned to a BCI group and a control group. All of them participated in rehabilitation training for four weeks and were assessed by the Fugl-Meyer Assessment (FMA) of motor function. Results. The average improvement score of the BCI group was 3.5, which was higher than that of the control group (0.9). The active EEG patterns of the four patients in the BCI group whose FMA scores increased gradually became centralized and shifted to sensorimotor areas and premotor areas throughout the study. Conclusions. Study results showed evidence that patients in the BCI group achieved larger functional improvements than those in the control group and that the BCI-FES system is effective in restoring motor function to upper extremities in stroke patients. This study provides a more autonomous approach than traditional treatments used in stroke rehabilitation.http://dx.doi.org/10.1155/2020/8882764 |
spellingShingle | Yangyang Miao Shugeng Chen Xinru Zhang Jing Jin Ren Xu Ian Daly Jie Jia Xingyu Wang Andrzej Cichocki Tzyy-Ping Jung BCI-Based Rehabilitation on the Stroke in Sequela Stage Neural Plasticity |
title | BCI-Based Rehabilitation on the Stroke in Sequela Stage |
title_full | BCI-Based Rehabilitation on the Stroke in Sequela Stage |
title_fullStr | BCI-Based Rehabilitation on the Stroke in Sequela Stage |
title_full_unstemmed | BCI-Based Rehabilitation on the Stroke in Sequela Stage |
title_short | BCI-Based Rehabilitation on the Stroke in Sequela Stage |
title_sort | bci based rehabilitation on the stroke in sequela stage |
url | http://dx.doi.org/10.1155/2020/8882764 |
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