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An Adaptive Brain-Computer Interface to Enhance Motor Recovery After Stroke

Authors :
Rui Zhang
Chushan Wang
Shenghong He
Chunli Zhao
Keming Zhang
Xiaoyun Wang
Yuanqing Li
Source :
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 2268-2278 (2023)
Publication Year :
2023
Publisher :
IEEE, 2023.

Abstract

Brain computer interfaces (BCIs) have been demonstrated to have the potential to enhance motor recovery after stroke. However, some stroke patients with severe paralysis have difficulty achieving the BCI performance required for participating in BCI-based rehabilitative interventions, limiting their clinical benefits. To address this issue, we presented a BCI intervention approach that can adapt to patients’ BCI performance and reported that adaptive BCI-based functional electrical stimulation (FES) treatment induced clinically significant, long-term improvements in upper extremity motor function after stroke more effectively than FES treatment without BCI intervention. These improvements were accompanied by a more optimized brain functional reorganization. Further comparative analysis revealed that stroke patients with low BCI performance (LBP) had no significant difference from patients with high BCI performance in rehabilitation efficacy improvement. Our findings suggested that the current intervention may be an effective way for LBP patients to engage in BCI-based rehabilitation treatment and may promote lasting motor recovery, thus contributing to expanding the applicability of BCI-based rehabilitation treatments to pave the way for more effective rehabilitation treatments.

Details

Language :
English
ISSN :
15580210
Volume :
31
Database :
Directory of Open Access Journals
Journal :
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.1d9a599f51a4ffbb998ed6ae246f494
Document Type :
article
Full Text :
https://doi.org/10.1109/TNSRE.2023.3272372