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

J Neuroeng Rehabil. 2025 Mar 3;22(1):44. doi: 10.1186/s12984-025-01588-x.

Abstract

Background: 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.

Objectives: 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.

Design: 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.

Data sources and methods: 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.

Results: 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.

Conclusions: BCI-based training may be a reliable rehabilitation program to improve upper-limb motor impairment and function.

Trial registration: PROSPERO registration ID: CRD42022383390.

Keywords: Brain-computer interface; Motor impairment; Rehabilitation; Stroke; Upper-limb.

Publication types

  • Meta-Analysis
  • Review

MeSH terms

  • Brain-Computer Interfaces*
  • Humans
  • Randomized Controlled Trials as Topic
  • Stroke / physiopathology
  • Stroke Rehabilitation* / methods
  • Upper Extremity* / physiopathology