Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis

Autor: Mingyue Liu, Mingzhu Fang, Mengya Liu, Shasha Jin, Bin Liu, Liang Wu, Zhe Li
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Human Neuroscience, Vol 18 (2024)
Druh dokumentu: article
ISSN: 1662-5161
DOI: 10.3389/fnhum.2024.1486167
Popis: BackgroundAlthough the application of brain-computer interface (BCI) technology in rehabilitation has been extensively studied, a systematic and comprehensive bibliometric analysis of this area remains lacking. Thus, this study aims to analyze the research progress of BCI technology in rehabilitation through bibliometric methods.MethodsThe study retrieved relevant publications on BCI technology in rehabilitation from the Web of Science Core Collection (WoSCC) between January 1, 2004, and June 30, 2024. The search was conducted using thematic queries, and the document types included “original articles” and “review articles.” Bibliometric analysis and knowledge mapping were performed using the Bibliometrix package in R software and CiteSpace software.ResultsDuring the study period, a total of 1,431 publications on BCI technology in rehabilitation were published by 4,932 authors from 1,281 institutions across 79 countries in 386 academic journals. The volume of research literature in this field has shown a steady upward trend. The United States of America (USA) and China are the primary contributors, with Eberhard Karls University of Tübingen being the most active research institution. The journal Frontiers in Neuroscience published the most articles, while the Journal of Neural Engineering was the most cited. Niels Birbaumer not only authored the most articles but also received the highest number of citations. The main research areas include neurology, sports medicine, and ophthalmology. The diverse applications of BCI technology in stroke and spinal cord injury rehabilitation, as well as the evaluation of BCI performance, are current research hotspots. Moreover, deep learning has demonstrated significant potential in BCI technology rehabilitation applications.ConclusionThis bibliometric study provides an overview of the research landscape and developmental trends of BCI technology in rehabilitation, offering valuable reference points for researchers in formulating future research strategies.
Databáze: Directory of Open Access Journals