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ArticleFrontiers in neurology

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.

Yaojiang Li, Yunhong Deng, Lixia Deng, Xiao Lu, Congping Huang, Xing Chen, Yunyi Liu, Peiling Chen, Mingjun Tang, Fuqiang Wang

Abstract read
In one paragraph

Article in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Yaojiang Li *Department of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Yunhong Deng *Department of Rehabilitation Therapy, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Lixia DengDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Xiao LuDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Congping HuangDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Xing ChenDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Yunyi LiuDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Peiling ChenDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Mingjun TangDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.
Fuqiang WangDepartment of Rehabilitation Medicine, Guangdong Sanjiu Brain Hospital, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

brain–computer interfacefeedback modenetwork meta-analysisstrokestudy protocolsystematic reviewupper limb function

Identifiers

PMID42591285
PMCPMC13461578

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.