ArticleJournal of multidisciplinary healthcare2025
A Bibliometric Analysis of the Application of Brain-Computer Interface in Rehabilitation Medicine Over the Past 20 Years.
Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of artificial intelligence in palliative care: a bibliometric analysis of research hotspots and trends.Frontiers in medicine · 2025Pooled it
- Global Trends in Research of Brain-Computer Interfaces in Neuroscience From 2014 to 2023: A Bibliometric Analysis.CNS neuroscience & therapeutics · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aims to conduct a bibliometric analysis of the application of brain- computer interface (BCI) in rehabilitation medicine, assessing the current state, developmental trends, and future potential of this field. By systematically analyzing relevant literature, we seek to identify key research themes and enhance understanding of BCI technology in rehabilitation. Methods: We utilized bibliometric analysis tools such as VOSviewer and CiteSpace to screen and analyze 426 relevant articles from the Web of Science Core Collection (WoSCC) database. We quantitatively evaluated citation patterns, publication trends, and the collaboration networks of research institutions and authors to uncover research hotspots and frontier dynamics in the field. Results: The findings indicate a continuous increase in research publications since 2003, with a notable peak occurring between 2019 and 2021. The analysis revealed that motor imagery, motor recovery, and signal processing are the predominant research themes. Furthermore, the United States and China are leading in the publication volume related to BCI and rehabilitation medicine. Key research institutions include the University of Tübingen and the New York State Department of Health, with significant contributions from scholars like Niels Birbaumer. Conclusion: Although the current research on BCI in rehabilitation medicine shows significant potential and efficacy, further exploration of certain research directions is needed, along with the promotion of interdisciplinary collaboration to comprehensively address complex real-world issues such as motor function impairment. Future research should focus on optimizing training models, enhancing technical feasibility, and exploring home rehabilitation applications to facilitate the broader adoption of BCI technology in rehabilitation medicine.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.