Mingyue Liu, Mingzhu Fang, Mengya Liu, Shasha Jin, Bin Liu, Liang Wu, Zhe Li
{"title":"康复领域脑机接口技术的知识图谱和研究趋势：文献计量分析。","authors":"Mingyue Liu, Mingzhu Fang, Mengya Liu, Shasha Jin, Bin Liu, Liang Wu, Zhe Li","doi":"10.3389/fnhum.2024.1486167","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Although 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.</p><p><strong>Methods: </strong>The 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.</p><p><strong>Results: </strong>During 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 <i>Frontiers in Neuroscience</i> published the most articles, while the <i>Journal of Neural Engineering</i> 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.</p><p><strong>Conclusion: </strong>This 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.</p>","PeriodicalId":12536,"journal":{"name":"Frontiers in Human Neuroscience","volume":"18 ","pages":"1486167"},"PeriodicalIF":2.4000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11557533/pdf/","citationCount":"0","resultStr":"{\"title\":\"Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis.\",\"authors\":\"Mingyue Liu, Mingzhu Fang, Mengya Liu, Shasha Jin, Bin Liu, Liang Wu, Zhe Li\",\"doi\":\"10.3389/fnhum.2024.1486167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Although 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.</p><p><strong>Methods: </strong>The 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.</p><p><strong>Results: </strong>During 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 <i>Frontiers in Neuroscience</i> published the most articles, while the <i>Journal of Neural Engineering</i> 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.</p><p><strong>Conclusion: </strong>This 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.</p>\",\"PeriodicalId\":12536,\"journal\":{\"name\":\"Frontiers in Human Neuroscience\",\"volume\":\"18 \",\"pages\":\"1486167\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11557533/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Human Neuroscience\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fnhum.2024.1486167\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Human Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fnhum.2024.1486167","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
Knowledge mapping and research trends of brain-computer interface technology in rehabilitation: a bibliometric analysis.
Background: Although 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.
Methods: The 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.
Results: During 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.
Conclusion: This 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.
期刊介绍：
Frontiers in Human Neuroscience is a first-tier electronic journal devoted to understanding the brain mechanisms supporting cognitive and social behavior in humans, and how these mechanisms might be altered in disease states. The last 25 years have seen an explosive growth in both the methods and the theoretical constructs available to study the human brain. Advances in electrophysiological, neuroimaging, neuropsychological, psychophysical, neuropharmacological and computational approaches have provided key insights into the mechanisms of a broad range of human behaviors in both health and disease. Work in human neuroscience ranges from the cognitive domain, including areas such as memory, attention, language and perception to the social domain, with this last subject addressing topics, such as interpersonal interactions, social discourse and emotional regulation. How these processes unfold during development, mature in adulthood and often decline in aging, and how they are altered in a host of developmental, neurological and psychiatric disorders, has become increasingly amenable to human neuroscience research approaches. Work in human neuroscience has influenced many areas of inquiry ranging from social and cognitive psychology to economics, law and public policy. Accordingly, our journal will provide a forum for human research spanning all areas of human cognitive, social, developmental and translational neuroscience using any research approach.
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