Brain-computer interface and functional electrical stimulation: a novel approach to motor rehabilitation in CNS injury patients

Central nervous system (CNS) injuries, such as stroke and spinal cord injury, often result in persistent motor impairments that conventional rehabilitation can only partially alleviate. Recent developments in brain-computer interfaces (BCIs) combined with functional electrical stimulation (FES) have introduced a novel approach to motor rehabilitation by directly linking cortical signals with specific muscle activation. This closed-loop system compensates for disrupted neural transmission and simultaneously promotes activity-dependent plasticity, thereby supporting functional reorganisation within the CNS. Findings from pilot trials and preclinical studies indicate that BCI-FES enhances motor recovery in both upper and lower limbs, increases patient engagement, and facilitates long-term cortical reorganisation. However, significant limitations persist, such as inconsistent neural decoding, stimulation-related fatigue, and the lack of standardised treatment protocols. Moreover, ethical challenges such as informed consent, neural data privacy, and equitable access must be resolved before broad clinical adoption can be achieved. Future research should focus on rigorous multicentre trials, tailored intervention strategies, and integration with emerging digital health technologies. This review synthesises current evidence on BCI-FES paradigms, stimulation parameters, underlying mechanisms, and ethical considerations, and outlines future directions to accelerate its clinical translation in CNS rehabilitation.

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Publication Details

Journal
International Journal of Surgery
Published
2025-12-11
DOI
https://doi.org/10.1097/js9.0000000000004392
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.43
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article

Brain-computer interface and functional electrical stimulation: a novel approach to motor rehabilitation in CNS injury patients

Jianmin Wu, Debin Guo, Jun Fei, Zi Wang et al.
1 citations
International Journal of Surgery
EEG and Brain-Computer Interfaces
1.43
article

Brain-computer interface and functional electrical stimulation: a novel approach to motor rehabilitation in CNS injury patients

Jianmin Wu, Debin Guo, Jun Fei, Zi Wang, Zhong Li, Li Lei, Hongliang Li, Jinghong Yang, Hao Jiang, Zheng Li, DU Yi-min
article en
1 citations

Abstract

Central nervous system (CNS) injuries, such as stroke and spinal cord injury, often result in persistent motor impairments that conventional rehabilitation can only partially alleviate. Recent developments in brain-computer interfaces (BCIs) combined with functional electrical stimulation (FES) have introduced a novel approach to motor rehabilitation by directly linking cortical signals with specific muscle activation. This closed-loop system compensates for disrupted neural transmission and simultaneously promotes activity-dependent plasticity, thereby supporting functional reorganisation within the CNS. Findings from pilot trials and preclinical studies indicate that BCI-FES enhances motor recovery in both upper and lower limbs, increases patient engagement, and facilitates long-term cortical reorganisation. However, significant limitations persist, such as inconsistent neural decoding, stimulation-related fatigue, and the lack of standardised treatment protocols. Moreover, ethical challenges such as informed consent, neural data privacy, and equitable access must be resolved before broad clinical adoption can be achieved. Future research should focus on rigorous multicentre trials, tailored intervention strategies, and integration with emerging digital health technologies. This review synthesises current evidence on BCI-FES paradigms, stimulation parameters, underlying mechanisms, and ethical considerations, and outlines future directions to accelerate its clinical translation in CNS rehabilitation.

International Journal of SurgeryVol. 112(3)
Army Medical University (CN), Southwest Medical University (CN), Affiliated Hospital of Southwest Medical University (CN), Daping Hospital (CN)
Openalex Percentile: Top 13%
EEG and Brain-Computer Interfaces
1.43
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