《中国康复理论与实践》 ›› 2023, Vol. 29 ›› Issue (2): 223-230.doi: 10.3969/j.issn.1006-9771.2023.02.011

• 循证研究 • 上一篇    下一篇

近10年脑机接口技术用于脑卒中康复领域的可视化分析

刘明月, 樊亚蕾, 张蒙, 宋薛艺, 李哲2,3()   

  1. 1.郑州大学第五附属医院,a.康复医学科;b.儿童康复科,河南郑州市 450052
    2.河南省康复医学重点试验室,河南郑州市 450052
    3.郑州大学康复医学研究所,河南郑州市 450052
  • 收稿日期:2022-08-12 修回日期:2023-01-06 出版日期:2023-02-25 发布日期:2023-03-16
  • 通讯作者: 李哲 E-mail:Lizhe.1974@163.com
  • 作者简介:刘明月(1994-),男,汉族,河南周口市人,硕士研究生,主要研究方向:脑机接口技术。
  • 基金资助:
    河南省医学科技攻关计划省部共建项目(SBGJ202002092)

Brain-computer interface technology for stroke in the past decade: a visualized analysis

LIU Mingyue, FAN Yalei, ZHANG Meng, SONG Xueyi, LI Zhe2,3()   

  1. 1. a.Department of Rehabilitation Medicine; b. Department of Child Rehabilitation, the Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450052, China
    2. Key Laboratory of Rehabilitation Medicine in Henan, Zhengzhou, Henan 450052, China
    3. Institute of Rehabilitation Medicine, Zhengzhou University, Zhengzhou, Henan 450052, China
  • Received:2022-08-12 Revised:2023-01-06 Published:2023-02-25 Online:2023-03-16
  • Contact: LI Zhe E-mail:Lizhe.1974@163.com
  • Supported by:
    Supported by Provincial Joint Construction Project of Henan Medical Science and Technology Research Program No.(SBGJ202002092)

摘要:

目的 对近10年脑机接口技术用于脑卒中康复领域的相关研究进行可视化分析,识别并预测研究热点及其演变趋势。方法 检索Web of Science核心合集数据库中2011年1月至2022年10月收录的脑机接口技术用于脑卒中康复领域的相关文献,通过CiteSpace 5.8.R3软件绘制发文量、国家、机构、作者、关键词、共被引以及基金支持的可视化图谱并进行解读。结果与结论 共纳入592篇文献。该领域研究年发文量呈快速增长趋势,研究热度持续增加。美国在此领域处于领先地位,合作发文量最多且中介中心性最高;中国在此领域具有一定的优势,但仍需加强与其他国家/地区间交流合作。国外机构、作者间形成交流密切的合作关系网络,并形成以Niels Birbaumer、Cuntai Guan、Kai Keng Ang等为代表的高影响力团队;国内作者、机构之间合作关系欠佳,存在地域限制,缺乏高影响力的学术团体。关键词以“motor imagery”“recovery”等为代表形成10个主要聚类和15个变化率高的突显词,研究方向呈现出多元化趋势。上肢运动康复的疗效研究和中枢机制探讨一直是该领域的热点,且在未来一段时间内仍将持续;下肢脑机接口系统用于改善脑卒中患者足下垂、步态和平衡功能,以及多模态脑机接口的应用,可能会发展为未来的研究热点;基于脑机接口引导的神经反馈训练用于脑卒中的认知、语言康复同样需要予以关注。

关键词: 脑机接口, 脑卒中, 康复, 知识图谱, 可视化分析

Abstract:

Objective To conduct a visualized analysis of the research related to the use of brain-computer interface technology for stroke rehabilitation in the past ten years, and identify and predict the hot spots and hot trends in order to promote the further development of this field. Methods The Web of Science Core Collection database was searched for literature related to brain-computer interface technology for stroke rehabilitation from January, 2011 to October, 2022. CiteSpace 5.8.R3 was used to analyze the number of publications, countries, institutions, authors, keywords, co-citations, and grant support. Results and Conclusion A total of 592 papers were included, and the annual number of publications in this field of research showed a rapid growth trend, and the research enthusiasm continued to increase. The United States was in the leading position in this field, with the highest number of cooperative publications and the highest intermediary centrality; China had certain advantages in this field, but still needed to strengthen the exchange and cooperation with other countries/regions. Foreign institutions and authors had formed a network of close cooperative relationships, and formed a high-impact team represented by Niels Birbaumer, Cuntai Guan, Kai Keng Ang, etc.; there were poor cooperative relationships among domestic authors and institutions, and there were geographical restrictions and lack of high-impact academic groups. The keywords "motor imagery" and "recovery" formed ten major clusters and 15 prominent words with high variation rates, showing a trend of diversification in research directions. The study of the efficacy of upper limb motor rehabilitation and central mechanisms has been the hot topics in this field and will continue for some time in the future; the use of lower limb brain-computer interface systems for improving foot drop, gait and balance in stroke patients and the application of multimodal brain-computer interfaces will probably become a hot topic in the future. Finally, the use of brain-computer interface-guided neurofeedback training for cognitive and language rehabilitation in stroke also needs attention.

Key words: brain-computer interface, stroke, rehabilitation, knowledge mapping, visualized analysis

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