Effects of brain-computer interface training on upper limb function recovery in stroke patients A protocol for systematic review and meta-analysis

被引:6
|
作者
Xue, Xiali [1 ]
Tu, Huan [1 ]
Deng, Zhongyi [1 ]
Zhou, Ling [2 ]
Li, Ning [1 ]
Wang, Xiaokun [3 ]
机构
[1] Chengdu Sport Univ, Inst Sports Med & Hlth, 2 Tiyuan Rd, Chengdu 610041, Sichuan, Peoples R China
[2] Chengdu Sport Univ, Sch Sports Med & Hlth, Chengdu, Sichuan, Peoples R China
[3] Peoples Hosp Mancheng Dist, Baoding, Hebei, Peoples R China
关键词
brain-computer interface; meta-analysis; protocol; stroke; upper limb function; ELECTRICAL-STIMULATION; HAND REHABILITATION; MACHINE INTERFACES; SPASTICITY;
D O I
10.1097/MD.0000000000026254
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background: In recent years, with the development of medical technology and the increase of inter-disciplinary cooperation technology, new methods in the field of artificial intelligence medicine emerge in an endless stream. Brain-computer interface (BCI), as a frontier technology of multidisciplinary integration, has been widely used in various fields. Studies have shown that BCI-assisted training can improve upper limb function in stroke patients, but its effect is still controversial and lacks evidence-based evidence, which requires further exploration and confirmation. Therefore, the main purpose of this paper is to systematically evaluate the efficacy of different BCI-assisted training on upper limb function recovery in stroke patients, to provide a reference for the application of BCI-assisted technology in stroke rehabilitation. Methods: We will search PubMed, Web of Science, The Cochrane Library, Chinese National Knowledge Infrastructure Database, Wanfang Data, Weipu Electronics, and other databases (from the establishment to February 2021) for full text in Chinese and English. Randomized controlled trials were collected to examine the effect of BCI-assisted training on upper limb functional recovery in stroke patients. We will consider inclusion, select high-quality articles for data extraction and analysis, and summarize the intervention effect of BCI-assisted training on the upper limb function of stroke patients. Two reviewers will screen titles, abstracts, and full texts independently according to inclusion criteria; Data extraction and risk of bias assessment were performed in the included studies. We will use a hierarchy of recommended assessment, development, and assessment methods to assess the overall certainty of the evidence and report findings accordingly. Endnote X8 will be applied in selecting the study, Review Manager 5.3 will be applied in analyzing and synthesizing. Results: The results will provide evidence for judging whether BCI is effective and safe in improving upper limb function in patients with stroke. Conclusion: Our study will provide reliable evidence for the effect of BCI technology on the improvement of upper limb function in stroke patients. PROSPERO registration number: CRD42021250378.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] The clinical effects of brain-computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review
    Qu, Hao
    Zeng, Feixiang
    Tang, Yongbin
    Shi, Bin
    Wang, Zhijun
    Chen, Xiaokai
    Wang, Jing
    DISABILITY AND REHABILITATION-ASSISTIVE TECHNOLOGY, 2024, 19 (01) : 30 - 41
  • [2] Verum versus Sham brain-computer interface on upper limb function recovery after stroke: A systematic review and meta-analysis of randomized controlled trials
    Shou, Yi-zhou
    Wang, Xin-hua
    Yang, Gui-fen
    MEDICINE, 2023, 102 (26) : E34148
  • [3] Effects of brain-computer interface based training on post-stroke upper-limb rehabilitation: a meta-analysis
    Li, Dan
    Li, Ruoyu
    Song, Yunping
    Qin, Wenting
    Sun, Guangli
    Liu, Yunxi
    Bao, Yunjun
    Liu, Lingyu
    Jin, Lingjing
    JOURNAL OF NEUROENGINEERING AND REHABILITATION, 2025, 22 (01)
  • [4] The effect of brain-computer interface controlled functional electrical stimulation training on rehabilitation of upper limb after stroke: a systematic review and meta-analysis
    Ren, Chunlin
    Li, Xinmin
    Gao, Qian
    Pan, Mengyang
    Wang, Jing
    Yang, Fangjie
    Duan, Zhenfei
    Guo, Pengxue
    Zhang, Yasu
    FRONTIERS IN HUMAN NEUROSCIENCE, 2024, 18
  • [5] The Application of Brain-Computer Interface in Upper Limb Dysfunction After Stroke: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
    Peng, Yang
    Wang, Jing
    Liu, Zicai
    Zhong, Lida
    Wen, Xin
    Wang, Pu
    Gong, Xiaoqian
    Liu, Huiyu
    FRONTIERS IN HUMAN NEUROSCIENCE, 2022, 16
  • [6] Effects of wearable device training on upper limb motor function in patients with stroke: a systematic review and meta-analysis
    Song, Qianqian
    Qin, Qin
    Suen, Lorna Kwai Ping
    Liang, Guangmei
    Qin, Haixia
    Zhang, Lingling
    JOURNAL OF INTERNATIONAL MEDICAL RESEARCH, 2024, 52 (10)
  • [7] Brain-Computer Interface Training Based on Brain Activity Can Induce Motor Recovery in Patients With Stroke: A Meta-Analysis
    Nojima, Ippei
    Sugata, Hisato
    Takeuchi, Hiroki
    Mima, Tatsuya
    NEUROREHABILITATION AND NEURAL REPAIR, 2022, 36 (02) : 83 - 96
  • [8] The Effect of Brain-Computer Interface Training on Rehabilitation of Upper Limb Dysfunction After Stroke: A Meta-Analysis of Randomized Controlled Trials
    Yang, Weiwei
    Zhang, Xiaoyun
    Li, Zhenjing
    Zhang, Qiongfang
    Xue, Chunhua
    Huai, Yaping
    FRONTIERS IN NEUROSCIENCE, 2022, 15
  • [9] Use of Electroencephalography Brain-Computer Interface Systems as a Rehabilitative Approach for Upper Limb Function After a Stroke: A Systematic Review
    Monge-Pereira, Esther
    Ibanez-Pereda, Jaime
    Alguacil-Diego, Isabel M.
    Serrano, Jose I.
    Spottorno-Rubio, Maria P.
    Molina-Rueda, Francisco
    PM&R, 2017, 9 (09) : 918 - 932
  • [10] Efficacy of brain-computer interfaces on upper extremity motor function rehabilitation after stroke: A systematic review and meta-analysis
    Zhang, Ming
    Zhu, Feilong
    Jia, Fan
    Wu, Yu
    Wang, Bin
    Gao, Ling
    Chu, Fengming
    Tang, Wei
    NEUROREHABILITATION, 2024, 54 (02) : 199 - 212