Li Dan, Li Ruoyu, Song Yunping, Qin Wenting, Sun Guangli, Liu Yunxi, Bao Yunjun, Liu Lingyu, Jin Lingjing
Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Persons' Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, , Tongji University, Shanghai, 201619, China.
Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, 200438, China.
J Neuroeng Rehabil. 2025 Mar 3;22(1):44. doi: 10.1186/s12984-025-01588-x.
Previous research has used the brain-computer interface (BCI) to promote upper-limb motor rehabilitation. However, the results of these studies were variable, leaving efficacy unclear.
This review aims to evaluate the effects of BCI-based training on post-stroke upper-limb rehabilitation and identify potential factors that may affect the outcome.
A meta-analysis including all available randomized-controlled clinical trials (RCTs) that reported the efficacy of BCI-based training on upper-limb motor rehabilitation after stroke.
We searched PubMed, Cochrane Library, and Web of Science before September 15, 2024, for relevant studies. The primary efficacy outcome was the Fugl-Meyer Assessment-Upper extremity (FMA-UE). RevMan 5.4.1 with a random effect model was used for data synthesis and analysis. Mean difference (MD) and 95% confidence interval (95%CI) were calculated.
Twenty-one RCTs (n = 886 patients) were reviewed in the meta-analysis. Compared with control, BCI-based training exerted significant effects on FMA-UE (MD = 3.69, 95%CI 2.41-4.96, P < 0.00001, moderate-quality evidence), Wolf Motor Function Test (WMFT) (MD = 5.00, 95%CI 2.14-7.86, P = 0.0006, low-quality evidence), and Action Research Arm Test (ARAT) (MD = 2.04, 95%CI 0.25-3.82, P = 0.03, high-quality evidence). Additionally, BCI-based training was effective on FMA-UE for both subacute (MD = 4.24, 95%CI 1.81-6.67, P = 0.0006) and chronic patients (MD = 2.63, 95%CI 1.50-3.76, P < 0.00001). BCI combined with functional electrical stimulation (FES) (MD = 4.37, 95%CI 3.09-5.65, P < 0.00001), robots (MD = 2.87, 95%CI 0.69-5.04, P = 0.010), and visual feedback (MD = 4.46, 95%CI 0.24-8.68, P = 0.04) exhibited significant effects on FMA-UE. BCI combined with FES significantly improved FMA-UE for both subacute (MD = 5.31, 95%CI 2.58-8.03, P = 0.0001) and chronic patients (MD = 3.71, 95%CI 2.44-4.98, P < 0.00001), and BCI combined with robots was effective for chronic patients (MD = 1.60, 95%CI 0.15-3.05, P = 0.03). Better results may be achieved with daily training sessions ranging from 20 to 90 min, conducted 2-5 sessions per week for 3-4 weeks.
BCI-based training may be a reliable rehabilitation program to improve upper-limb motor impairment and function.
PROSPERO registration ID: CRD42022383390.
以往研究利用脑机接口(BCI)促进上肢运动康复。然而,这些研究结果参差不齐,疗效尚不清楚。
本综述旨在评估基于BCI的训练对脑卒中后上肢康复的影响,并确定可能影响结果的潜在因素。
一项荟萃分析,纳入所有报告了基于BCI的训练对脑卒中后上肢运动康复疗效的随机对照临床试验(RCT)。
我们于2024年9月15日前在PubMed、Cochrane图书馆和科学网搜索相关研究。主要疗效指标为Fugl-Meyer上肢评估量表(FMA-UE)。采用随机效应模型的RevMan 5.4.1进行数据合成和分析。计算平均差(MD)和95%置信区间(95%CI)。
荟萃分析纳入了21项RCT(n = 886例患者)。与对照组相比,基于BCI的训练对FMA-UE(MD = 3.69, 95%CI 2.41 - 4.96, P < 0.00001,中等质量证据)、Wolf运动功能测试(WMFT)(MD = 5.00, 95%CI 2.14 - 7.86, P = 0.0006,低质量证据)和动作研究上肢测试(ARAT)(MD = 2.04, 95%CI 0.25 - 3.82, P = 0.03,高质量证据)有显著影响。此外,基于BCI的训练对亚急性期(MD = 4.24, 95%CI 1.81 - 6.67, P = 0.0006)和慢性期患者(MD = 2.63, 95%CI 1.50 - 3.76, P < 0.00001)的FMA-UE均有效。BCI联合功能性电刺激(FES)(MD = 4.37, 95%CI 3.09 - 5.65, P < 0.00001)、机器人(MD = 2.87, 95%CI 0.69 - 5.04, P = 0.010)和视觉反馈(MD = 4.46, 95%CI 0.24 - 8.68, P = 0.04)对FMA-UE有显著影响。BCI联合FES对亚急性期(MD = 5.31, 95%CI 2.58 - 8.03, P = 0.0001)和慢性期患者(MD = 3.71, 95%CI 2.44 - 4.98, P < 0.00001)的FMA-UE均有显著改善,BCI联合机器人对慢性期患者有效(MD = 1.60, 95%CI 0.15 - 3.05, P = 0.03)。每周进行2 - 5次、每次20 - 90分钟、持续3 - 4周的日常训练可能会取得更好的效果。
基于BCI的训练可能是改善上肢运动障碍和功能的可靠康复方案。
PROSPERO注册号:CRD42022383390。