Multifunctional Integration Rehabilitation Brain-Computer Interface for Stroke: Application Exploration and New Horizons
JIA Jie1,2,3,4
1Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
2Department of Rehabilitation Medicine, Fujian Hospital, Huashan Hospital, Fudan University, Fuzhou 350600, China
3Department of Rehabilitation Medicine, Shanghai Jing’an District Central Hospital, Shanghai 200040, China
4National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China
JIA Jie. Multifunctional Integration Rehabilitation Brain-Computer Interface for Stroke: Application Exploration and New Horizons[J]. Chinese Journal of Stroke, 2026, 21(3): 257-262.
[1]NAVARRO-SUNE X,HUDSON A L,DE VICO FALLANI F,et al. Riemannian geometry applied to detection of respiratory states from EEG signals:the basis for a brain-ventilator interface[J]. IEEE Trans Biomed Eng,2017,64(5):1138-1148.
[2] 贾杰. 卒中康复脑机接口全周期模式的思考与构建[J]. 中国卒中杂志,2025,20(10):1203-1208.
JIA J. Reflection and construction of the full-cycle model of stroke rehabilitation brain-computer interface[J]. Chin J Stroke,2025,20(10):1203-1208.
[3] LIU Y,LI M F,ZHANG H,et al. Single-trial discrimination of EEG signals for stroke patients:a general multi-way analysis[J/OL]. Annu Int Conf IEEE Eng Med Biol Soc,2013:2204-2207[2025-12-25]. https://doi.org/10.1109/EMBC.2013.6609973.
[4] SHEN C W,NAMIKI A. A topology-aware multiscale feature fusion network for EEG-based motor imagery decoding[J/OL]. Knowledge-Based Systems,330,Part A,114540[2025-12-25]. https://doi.org/10.1016/j.knosys.2025.114540.
[5] CAI X R,XUE C,CAO L,et al. A novel brain-computer interface application:precise decoding of urination and defecation motor attempts in spinal cord injury patients[J/OL]. IEEE Trans Neural Syst Rehabil Eng,2026,34:92-102[2026-02-25]. https://doi.org/10.1109/TNSRE.2025.3637066.
[6] ROS T,MICHELA A,BELLMAN A,et al. Increased alpha-rhythm dynamic range promotes recovery from visuospatial neglect:a neurofeedback study[J/OL]. Neural Plast,2017:7407241[2026-02-25]. https://doi.org/10.1155/2017/7407241.
[7] WANG P,LIU J Y,WANG L L,et al. Effects of brain-computer interface combined with mindfulness therapy on rehabilitation of hemiplegic patients with stroke:a randomized controlled trial[J/OL]. Front Psychol,2023,14:124108[2025-12-25]. https://doi.org/10.3389/fpsyg.2023.1241081.
[8] ZHANG X L,CAO D,LIU J N,et al. Effectiveness and safety of brain-computer interface technology in the treatment of poststroke motor disorders:a protocol for systematic review and meta-analysis[J/OL]. BMJ Open,2021,11(1):e042383[2025-12-25]. https://doi.org/10.1136/bmjopen-2020-042383.
[9] FU J H,CHEN S G,JIA J. Sensorimotor rhythm-based brain-computer interfaces for motor tasks used in hand upper extremity rehabilitation after stroke:a systematic review[J/OL]. Brain sciences,2022,13(1):56[2025-12-25]. https://doi.org/10.3390/brainsci13010056.
[10] ZHAN G G,CHEN S G,JI Y Y,et al. EEG-based brain network analysis of chronic stroke patients after BCI rehabilitation training[J/OL]. Front Hum Neurosci,2022,16:909610[2025-12-25]. https://doi.org/10.3389/fnhum.2022.909610.
[11] FU J H,CHEN S G,SHU X K,et al. Functional-oriented,portable brain-computer interface training for hand motor recovery after stroke:a randomized controlled study[J/OL]. Front Neurosci,2023,17:1146146[2025-12-25]. https://doi.org/10.3389/fnins.2023.1146146.
[12] 赵继宗. 临床神经科学在脑机接口临床研究中的担当与责任[J]. 中华医学杂志,2024,104(23):2102-2104.
ZHAO J Z. The role and responsibility of clinical neuroscience in brain-computer interface clinical research[J]. Natl Med J China,2024,104(23):2102-2104.
[13] HUO C C,ZHENG Y,LU W W,et al. Prospects for intelligent rehabilitation techniques to treat motor dysfunction[J]. Neural Regen Res,2021,16(2):264-269.
[14] LIN P J,LI W,ZHAI X X,et al. Explainable deep-learning prediction for brain-computer interfaces supported lower extremity motor gains based on multistate fusion[J/OL]. IEEE Trans Neural Syst Rehabil Eng,2024,32:1546-1555[2025-12-25]. https://doi.org/10.1109/TNSRE.2024.3384498.
[15] IRIMIA D C,CHO W,ORTNER R,et al. Brain-computer interfaces with multi-sensory feedback for stroke rehabilitation:a case study[J/OL]. Artif Organs,2017,41(11):E178-E184[2025-12-25]. https://doi.org/10.1111/aor.13054.
[16] LÓPEZ-LARRAZ E,MONTESANO L,GIL-AGUDO Á,et al. Continuous decoding of movement intention of upper limb self-initiated analytic movements from pre-movement EEG correlates[J/OL]. J Neuroeng Rehabil,2014,11:153[2025-12-25]. https://doi.org/10.1186/1743-0003-11-153.
[17] CAO P L,GUO S J,ZHANG G L,et al. Brain-computer interface training for multimodal functional recovery in patients with brain injury:a case series[J]. Quant Imaging Med Surg,2025,15(10):9277-9293.
[18]MANE R,WU Z Z,WANG D. Poststroke motor,cognitive and speech rehabilitation with brain-computer interface:a perspective review[J]. Stroke Vasc Neurol,2022,7(6):541-549.