文章摘要
王彬 ，吴炼铧 ，刘小平 ，周娅 ，王大明 ，胡东霞.脑机接口技术运用于脊髓损伤康复领域的可视化分析[J].神经损伤功能重建,2024,(7):402-407
脑机接口技术运用于脊髓损伤康复领域的可视化分析
Brain-Computer Interface Technology in Spinal Cord Injury Rehabilitation: A Bibliometric andVisualization Analysis
  
DOI：
中文关键词: 脑机接口  脊髓损伤  康复  可视化分析
英文关键词: brain-computer interface  spinal cord injury  rehabilitation  visualization analysis
基金项目:江西省工信厅优 势创新团队项目 （No. G/Y2738）； 江西省中医药管 理局科技计划项 目（No. 2021Z01 8，No. 2023B082 4）；江西省卫生 健康委员会科技 计划项目（No. 2 0171BBG70016）
作者单位
王彬1 ，吴炼铧1 ，刘小平1 ，周娅2 ，王大明3 ，胡东霞1 1. 南昌大学第二 附属医院康复医 学科 2. 昆明医科大学 康复学院 3. 浙江大学医学 院附属第一医院 
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中文摘要:
      目的：对脑机接口技术（BCI）运用于脊髓损伤（SCI）康复领域相关文献的研究现状、热点和发展趋势进 行可视化分析。方法：检索从建库至2023 年7月30日Web of Science 核心合集数据库中BCI技术运用于SCI 领域的相关文献，采用CiteSpace 6.1.R6 和Microsoft Excel 2023软件对数据进行可视化分析。结果：最终文献 计量分析纳入400篇文献，其中期刊类论文310 篇，综述类90 篇。过去二十年该领域文献的年发文量呈现快 速增长趋势。发文量最多的国家、作者和机构分别是美国、Collinger Jennifer L、Graz University Technology， 共被引次数最高的期刊是 J Neural Eng。以“functional electrical stimulation”、“movement”、“motor imagery” 等频次较高的关键词为代表形成 15 个主要聚类和前 16 个爆发力最强的突显词，其中“restoration”、“interface”、“walking”、“gait”等从2018 年开始持续至今，未来可能是研究趋势。结论：BCI技术运用于SCI康复领 域研究热度持续增加，目前疗效上主要集中于对SCI导致四肢瘫患者上肢运动和手抓握功能的恢复；中枢机 制上是诱导SCI后神经可塑性。未来的研究趋势和热点是探究BCI技术在改善SCI患者下肢步行或步态功 能的康复效果及其疗效机制。
英文摘要:
      To conduct a visualization analysis of the research status, hotspots, and development trends of brain-computer interface (BCI) technology in the rehabilitation of spinal cord injury (SCI) patients. Methods: Relevant literature about BCI technology applications in SCI was retrieved from the Web of Science Core Collection database from its inception to July 30, 2023. The data were subjected to bibliometric analysis using CiteSpace 6.1.R6 and Microsoft Excel 2023 software. Results: A total of 400 articles were included in the bibliometric analysis, including 310 journal articles and 90 reviews. The annual publication of literature in this field has shown an increasing trend over the past two decades. The most productive country, author and institution is the United States, Collinger Jennifer L, and Graz University Technology, respectively. The journal with the highest citation is J Neural Eng. High-frequency keywords such as "functional electrical stimulation", "movement" and "motor imagery" were identified, leading to 15 major clusters and 16 prominent burst terms. Notably, terms like "restoration", "interface", "walking", and "gait" have been continuously prominent since 2018, indicating potential future research trends. Conclusion: The application of BCI technology in SCI rehabilitation continues to increase in research popularity. The current efficacy mainly focuses on the recovery of upper limb movement and hand grip function in quadriplegia patients caused by SCI, with the central mechanism focusing on inducing neuroplasticity after SCI. Future research trends and hotspots are likely to explore the rehabilitation efficacy and underlying mechanisms of BCI technology in improving the walking or gait function of lower limbs in patients with SCI.
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