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Network meta-analysis protocol plans to evaluate brain-computer interface feedback modes for post-stroke upper-limb motor impairmentNew Plan to Compare Brain Computer Interfaces for Stroke Recovery

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Key Takeaway
Note that this is a study protocol; no clinical data or outcomes have been analyzed yet.

This publication is a protocol for a planned systematic review and network meta-analysis. It outlines the methodology to evaluate the efficacy of brain-computer interface (BCI) training with various feedback modes for patients with post-stroke upper-limb motor impairment.

The proposed analysis will compare BCI training involving functional electrical stimulation, robot- or exoskeleton-assisted feedback, visual feedback, virtual reality feedback, and combined multimodal feedback. These interventions will be compared against conventional rehabilitation, sham BCI, no additional intervention, and other active interventions. The primary outcome measure is the Fugl-Meyer Assessment for Upper Extremity (FMA-UE) score.

A significant limitation is that this is a protocol only; no data from clinical trials have been analyzed yet. Consequently, no conclusions regarding the efficacy or safety of BCI training can be drawn at this time. The study's results will eventually inform the comparative effectiveness of different feedback modalities in stroke rehabilitation.

How this fits prior evidence

This protocol addresses a gap in evidence regarding specific brain-computer interface (BCI) feedback modes for post-stroke upper-limb motor impairment. While prior coverage has addressed pharmacological interventions like liraglutide to reduce stroke recurrence and mechanical interventions such as Tigertriever for reperfusion, this study focuses on rehabilitative technology. No results are currently available from this protocol.

Researchers have developed a plan for a large study called a network meta-analysis. This study will look at how brain-computer interface (BCI) training helps people who have lost movement in their arms or hands after a stroke. The goal is to see which type of feedback works best for these patients.

The researchers plan to compare several types of BCI systems. These include methods that use electrical stimulation, robotic assistance, visual cues, and virtual reality. They will compare these against standard physical therapy and other common treatments to see if the technology provides better results.

Because this is currently a protocol for a planned study, no actual data has been collected or analyzed yet. The final results are not available at this time. This plan serves as a roadmap for future research to determine which specific technologies might best help stroke survivors regain their mobility.

What this means for you:
This is a plan for a future study; no results are currently available regarding the effectiveness of these tools.

Study Details

Study typeMeta analysis
EvidenceLevel 1
PublishedJul 2026
View Original Abstract ↓
BackgroundUpper 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.MethodsThis 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.ConclusionThis 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 registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD420261370474.
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