Comparative efficacy of brain-computer interface-coupled robotic rehabilitation, robot-assisted therapy, and motor imagery for upper-limb motor recovery after stroke: a systematic review and network meta-analysis

Why clinicians should know about it

• Picked for Rehabilitation (paper of the day, 26 September 2026): Network meta‑analysis of BCI‑robot vs robot therapy post‑stroke

Abstract

OBJECTIVE: To compare and rank the efficacy of brain-computer interface-coupled robotic rehabilitation (BCI-robot), robot-assisted therapy, motor imagery (MI), and conventional rehabilitation for upper-limb recovery after stroke, and to explore whether treatment effects differed according to key clinical and intervention-related characteristics. METHODS: A systematic search was conducted in 11 databases from inception to March 31, 2026. Randomized controlled trials enrolling adults with post-stroke upper-limb motor impairment were included. The primary outcome was the Fugl-Meyer Assessment of Upper Extremity (FMA-UE). Secondary outcomes included the Action Research Arm Test (ARAT), Wolf Motor Function Test (WMFT), and Modified Barthel Index (MBI). Direct pairwise meta-analyses were performed using mean differences (MDs) with 95% confidence intervals (CIs), and a frequentist network meta-analysis was conducted to synthesize direct and indirect evidence and rank interventions using P-scores. RESULTS: Twenty-three reports representing 22 independent study cohorts were included, comprising 727 participants. Network meta-analysis showed no significant inconsistency, and the consistency model was adopted. BCI-robot ranked highest for improving FMA-UE according to the P-score analysis (P-score = 0.992), followed by robot-assisted therapy (0.641), MI (0.240), and conventional rehabilitation (0.127). In direct comparisons, BCI-robot produced a statistically significant improvement in FMA-UE versus conventional rehabilitation (MD = 6.80, 95% CI 4.29 to 9.30). The point estimate exceeded the 5.25-point (minimal clinically important difference) MCID, although the lower confidence limit did not. Compared with robot-assisted therapy, BCI-robot showed a statistically significant but small improvement (MD = 2.04, 95% CI 0.29 to 3.78), with both the point estimate and the entire 95% CI remaining below the MCID. Follow-up-duration subgroup analyses suggested that BCI-robot remained favorable over conventional rehabilitation in both < 3-month and ≥ 3-month subgroups, whereas no significant follow-up advantage over robot-assisted therapy was observed. For secondary outcomes, BCI-robot significantly improved WMFT versus conventional rehabilitation (MD = 8.94, 95% CI 5.22 to 12.65) and MBI versus conventional rehabilitation (MD = 3.37, 95% CI 0.10 to 6.63). A significant benefit for MBI versus robot was also observed (MD = 8.61, 95% CI 1.76 to 15.46), although this result was not robust in sensitivity analysis. No significant advantage was found for ARAT. Exploratory subgroup analyses suggested that, compared with robot-assisted therapy, the additional benefit of BCI-robot was more apparent in studies delivering more than four sessions per week. CONCLUSIONS: BCI-robot ranked highest for improving FMA-UE and may provide a clinically important benefit over conventional rehabilitation, although the magnitude remains uncertain. Its additional benefit over robot-assisted therapy was small and unlikely to be clinically important. Evidence for longer-term effects and for activity-level and daily-function outcomes remains limited, and the findings should be interpreted cautiously.

Abstract as published, via PubMed.