Evidence map›Paper›PMID 41840816›Full record

ReviewMedical science monitor : international medical journal of experimental and clinical research2026

Application and Research Progress of BCI in Post-Stroke Psychiatric Disorders: A Narrative Review.

Zekai Hu, Jinyan Wang, Kun Zhou, Sicong Ma, Jun Hu

Abstract readReview
In one paragraph

Review in Medical science monitor : international medical journal of experimental and clinical research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zekai HuDepartment of Rehabilitation Medicine, Shanghai Second Rehabilitation Hospital, Shanghai, China.ORCID 0009-0009-2235-6693
Jinyan WangDepartment of Rehabilitation Medicine, Shanghai Second Rehabilitation Hospital, Shanghai, China.
Kun ZhouDepartment of Rehabilitation Medicine, Shanghai Zhongye Hospital, Shanghai, China.ORCID 0009-0004-9818-7295
Sicong MaDepartment of Rehabilitation Medicine, Shanghai Second Rehabilitation Hospital, Shanghai, China.
Jun HuDepartment of Rehabilitation Medicine, Shanghai Second Rehabilitation Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Post-stroke psychiatric disorders (PSPD), including depression, anxiety, and cognitive impairment, significantly hinder stroke survivors' rehabilitation and quality of life, with traditional interventions often showing limited efficacy. Brain-computer interface (BCI) technology has emerged as a promising tool for neurological regulation and rehabilitation, showing substantial potential in PSPD assessment and intervention. This narrative review comprehensively synthesizes the latest research advances in BCI applications for PSPD, covering underlying mechanisms, principal applications, clinical studies, technical challenges, and prospective directions. It highlights BCI's substantial potential in objective assessment, targeted neuromodulation, and promotion of neuroplasticity, while also addressing unresolved issues such as heterogeneous patient responses, technical limitations, and integration into routine clinical practice. By integrating current evidence and clarifying both achievements and gaps, this review provides theoretical insights and practical guidance for future basic and clinical research in the field.

Indexed as

Brain-Computer InterfacesMental DisordersStrokeStroke RehabilitationHumansNeuronal PlasticityQuality of Life

Identifiers

PMID41840816
PMCPMC13005422

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.