Different feedback modes of brain–computer interface training for upper limb motor function after stroke: a protocol for a systematic review and network meta-analysis
This study protocol specifies the methods for comparing different BCI feedback modes in post-stroke upper-limb rehabilitation and provides a transparent framework for the planned systematic review and network meta-analysis.
Abstract
Background Upper limb motor impairment after stroke is a major contributor to long-term disability and can have lasting effects on patients’ activities of daily living, social participation, and quality of life. Brain-computer interface (BCI) training establishes a closed-loop training process that links central nervous system activity, external feedback, and sensory reafferent input, and is considered a promising approach to facilitating neuroplastic reorganization and motor recovery. Existing studies on upper-limb rehabilitation after stroke have investigated several BCI feedback modes. However, the relative efficacy of these feedback modes has not been systematically compared across available randomized controlled trials. Methods This study protocol has been registered in PROSPERO with registration number CRD420261370474 and will be conducted in accordance with the PRISMA-P statement and the PRISMA-NMA extension. PubMed, Embase, Web of Science, the Cochrane Library, and Scopus will be systematically searched from inception to March 2026. Only parallel-group randomized controlled trials will be eligible for inclusion. Participants will be patients with post-stroke upper-limb motor impairment. The experimental interventions will consist of BCI training with different feedback modes, and intervention nodes will be defined according to specific feedback categories, including functional electrical stimulation, robot- or exoskeleton-assisted feedback, visual feedback, virtual reality feedback, and combined multimodal feedback. Control groups will include conventional rehabilitation, sham BCI, no additional intervention, and other active interventions. The primary outcome will be the Fugl-Meyer Assessment for Upper Extremity (FMA-UE) score. The secondary outcomes will be the Action Research Arm Test (ARAT) score and the Wolf Motor Function Test (WMFT) score. Two reviewers will independently perform study selection, data extraction, and risk-of-bias assessment, and any disagreements will be resolved through discussion or adjudication by a third reviewer. If the evidence network is sufficiently connected, a network meta-analysis will be performed to compare the relative efficacy across different intervention nodes. Local inconsistency will be assessed using the node-splitting method, and the surface under the cumulative ranking curve (SUCRA) will be used to rank different feedback modes according to efficacy. Conclusion This protocol specifies the methods for comparing different BCI feedback modes in post-stroke upper-limb rehabilitation and provides a transparent framework for the planned systematic review and network meta-analysis. Systematic review registration https://www.crd.york.ac.uk/prospero/, identifier CRD420261370474.
With respect to stroke staging, BCI-mediated rehabilitation interventions conferred superior efficacy for motor function recovery in patients with subacute stroke, a finding plausibly attributable to the temporal course of post-stroke neural remodeling.
Huanhuan Zhang, Runzhi Xian, Yuchi Zhang et al.· Journal of NeuroEngineering...· 0 citations
Abstract Background Noninvasive brain-computer interface (BCI)–based interventions show promise for poststroke motor recovery. However, the intrinsic complexity of BCI-based interventions limits the determination of their comparative efficacy. Objective Guided by the International Classification of Functioning, Disability and Health framework, this review evaluated the effectiveness of BCI-based interventions in poststroke upper limb rehabilitation and identify the optimal intervention. Methods We searched PubMed, Cochrane Library, EBSCOhost, Web of Science, Embase, Wiley Online Library,CNKI, Wanfang, VIP, and SinoMed through July 2026. Randomized controlled trials (RCTs) assessing BCI-based interventions for poststroke upper limb rehabilitation were included. Outcomes were body functions and structures (Fugl-Meyer Assessment of Upper Extremity [FMA-UE]) and activities and participation (Action Research Arm Test [ARAT], Wolf Motor Function Test [WMFT], and Modified Barthel Index [MBI]). Risk of bias was assessed using Cochrane RoB 2, and evidence quality was graded using the Grading of Recommendations, Assessment, Development, and Evaluation framework. We used pairwise meta-analyses to evaluate the overall effectiveness of BCI-based interventions vs controls and network meta-analysis to compare the interventions. Results Seventy-two RCTs involving 2906 patients with stroke were included, evaluating 12 BCI-based interventions. Pairwise meta-analyses demonstrated that, compared with control groups, BCI-based interventions improved FMA-UE (mean difference [MD] 5.33, 95% CI 4.28 to 6.38; 95% prediction interval [PI] −1.76 to 12.43), ARAT (MD 5.26, 95% CI 3.90 to 6.62; 95% PI 0.41 to 10.11), WMFT (MD 7.25, 95% CI 5.06 to 9.44; 95% PI 0.71 to 13.79), and MBI (MD 8.18, 95% CI 6.04 to 10.32; 95% PI −1.87 to 18.23). Network meta-analysis revealed that BCI-motor imagery-transcutaneous electrical acupoint stimulation (BCI-MI-TEAS) achieved the highest surface under the cumulative ranking curve (SUCRA; 95.5%) in improving FMA-UE. For ARAT, BCI-MI–end-effector robots and transcranial direct current stimulation (tDCS; 86.3%) alongside BCI-MI-TEAS (86.3%) yielded the highest SUCRA. BCI-MI–exoskeleton robot showed the highest SUCRA for WMFT (92.7%), whereas BCI-MI-TEAS (85.3%) and BCI-MI–exoskeleton robot (81.7%) ranked highest for MBI. The evidence quality ranged from very low to high across these interventions. Conclusions This study represents the first network meta-analysis comparing the efficacy of different BCI-based interventions. Unlike previous reviews, interventions were categorized by experimental paradigms, external feedback devices, and adjunctive noninvasive brain stimulation, to enable clinically meaningful comparisons. Overall, BCI-based interventions significantly improved poststroke upper limb rehabilitation. Among evaluated interventions, BCI-MI-TEAS demonstrated the most performance across body functions, structures, and activities and participation, whereas BCI-MI–end-effector robot + tDCS showed advantages for fine motor dexterity and BCI-MI–exoskeleton robot improved activities of daily living.Given low to moderate evidence certainty and substantial heterogeneity, these findings remain exploratory. High-quality trials are needed to establish the clinical utility of these interventions.
Jia-Bin Xu, Yitian Gao, Si-Qi Xie et al.· Journal of Medical Internet...· 0 citations
BCI-based training effectively improves lower-limb motor recovery after stroke, and subgroup analyses suggested that a moderate total dose combined with 20-40-minute sessions may represent a potentially optimal regimen, although these findings are based on limited RCTs and require confirmation in larger studies.
Xingyu Liu, Peng Huang, L. Wu et al.· Journal of Stroke & Cerebrov...· 0 citations
MI-BCI training can improve upper limb motor function, particularly for isolated movements and fine motor control, in stroke patients, but the current evidence does not support definitive conclusions regarding its superiority over standardised traditional rehabilitation.
Zhen Yang, Shan Zhang, Du Wang et al.· Brain Impairment· 0 citations
Overall, the certainty of evidence was low to very low, downgraded primarily for these risk of bias concerns, severe imprecision (due to small sample sizes), and potential publication bias.
Yu Qin, Mei-xuan Li, Yan-fei Li et al.· Cochrane Database of Systema...· 0 citations
Background: Upper limb motor impairment is a major contributor to long-term disability after stroke. Mirror therapy (MT) promotes motor relearning through visuomotor feedback, whereas transcranial direct current stimulation (tDCS) may facilitate neuroplasticity by modulating cortical excitability. We conducted a systematic review and meta-analysis to evaluate whether MT combined with tDCS provides additional benefits for poststroke upper limb rehabilitation. Methods: We searched PubMed, Embase, Web of Science, the Cochrane Library, CNKI, and Wanfang for randomized controlled trials (RCTs) published from 2015 to November 2025. Eligible studies enrolled adults with stroke-related upper limb motor deficits and compared MT + tDCS with MT alone or tDCS alone. Results: Twelve RCTs involving 1024 participants were included. For Fugl-Meyer Assessment for Upper Extremity, MT + tDCS showed superior improvement versus MT alone (3 studies; I-squared statistic (I2) = 21.9%; MD = 12.65, 95% confidence interval [CI] 10.07–15.23) and versus tDCS alone (7 studies; I2 = 93.3%; MD = 7.03, 95% CI 3.76–10.31). For activities of daily living, the effect on Modified Barthel Index versus MT alone was highly heterogeneous and imprecise (2 studies; I2 = 94.7%; MD = 24.19, 95% CI − 144.99 to 193.38), whereas MT + tDCS significantly improved Modified Barthel Index versus tDCS alone (5 studies; I2 = 42.7%; MD = 9.29, 95% CI 6.36–12.22). For hand function, MT + tDCS improved Wolf Motor Function Test versus tDCS alone (3 studies; I2 = 80.3%; MD = 4.90, 95% CI 0.59–9.22). Reported adverse events were generally mild and transient. Conclusion: MT combined with tDCS appears to provide additional benefits for poststroke upper limb motor recovery, with consistent improvements in Fugl-Meyer Assessment for Upper Extremity and favorable effects on daily functioning and hand performance in key comparisons. However, heterogeneity across protocols and imprecision in some outcomes limit certainty. Larger, rigorously designed RCTs with standardized MT dosing and tDCS parameters and longer follow-up are warranted.
Beibei Zong, Chun Zhang, Qingsha Zhang· Medicine· 0 citations