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Effects of brain-computer interface based training on post-stroke upper-limb rehabilitation: a meta-analysis

Dan Li, Ruoyu Li, Yun-Ping Song, Wenting Qin, Guiyang Sun, Yunxi Liu, Yunjun Bao, Lingyu Liu et al.

Journal of NeuroEngineering and Rehabilitation, 2025

886 participants · 44 citations

Abstract

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…

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Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 886 participants or records.

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