Evidence map›Paper›PMID 42499509›Full record

SynthesisFrontiers in neuroscience2026

Evolution of brain-computer interface technologies for stroke rehabilitation: a bibliometric integration of neural decoding and functional recovery (2016-2025).

Yutong Pan, Yiyang Huang, Mingming Bao, Xiandong Sun

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in neuroscience, 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

4 authors.

Yutong PanOccupational Therapy, Massachusetts College of Pharmacy and Health Sciences, Worcester, MA, United States.
Yiyang HuangRehabilitation Therapy, Clinical Medical College of Tianjin Medical University, Tianjin, China.
Mingming BaoDepartment of Rehabilitation Medicine, Chifeng Municipal Hospital, Chifeng, Inner Mongolia, China.
Xiandong SunDepartment of Hypertension Center, Chifeng Municipal Hospital, Chifeng, Inner Mongolia, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Brain-computer interface (BCI) technology represents a critical frontier in neurorehabilitation. This study aims to systematically analyze the global research landscape, hotspot distribution, and evolving trends of BCI interventions for upper limb rehabilitation in stroke survivors between 2016 and 2025. Methods: Bibliometric analysis and systematic mapping were conducted using data from the Web of Science Core Collection and PubMed. Literature was retrieved using terms related to "stroke," "brain-computer interface," and "upper limb rehabilitation." Screening followed the PRISMA guidelines. Visualization and quantitative mapping were performed using CiteSpace (v.6.4.R2) and VOSviewer (v.1.6.20) to evaluate publication volume, international collaboration, and keyword co-occurrence clusters. Results: Annual publications increased steadily from 37 in 2016 to 104 in 2025, with 65.6% published since 2020. The United States ( Discussion: BCI research for post-stroke recovery is transitioning from experimental signal processing to intelligent, multi-modal, and personalized clinical systems. Bibliometric evidence confirms that integrating BCI with robotic-assisted rehabilitation or functional electrical stimulation (FES) has become the mainstream clinical trend. Future efforts must focus on improving EEG signal stability and developing user-friendly hardware to facilitate the transition of BCI from research settings to daily clinical practice. China has emerged as the second most productive country, though international cooperation with European institutions remains an area for further growth.

Indexed as

artificial intelligencebibliometricsbrain-computer interfaceneuroplasticityrehabilitationrobotsstrokeupper limb

Identifiers

PMID42499509
PMCPMC13396001

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.