2015年至2025年数字健康技术在脑卒中上肢运动功能康复中应用的文献计量分析OA
Application of digital health technologies in upper limb motor function rehabilitation after stroke from 2015 to 2025:a bibliometric analysis
目的 分析数字健康技术(DHT)应用于脑卒中上肢运动功能康复领域的研究现状、热点和未来趋势. 方法 检索2015年1月至2025年12月Web of Science核心合集、中国知网和万方数据库中的有关DHT应用于脑卒中上肢运动康复领域的文献.采用CiteSpace 6.4.R1进行可视化分析. 结果 共纳入1 295篇文献,其中中文454篇,英文841篇,年发文量总体呈上升趋势.英文文献中,中国是发文量最多的国家,发文量最多的机构分别是复旦大学附属华山医院和苏黎世联邦理工学院;中、英文关键词均形成10个聚类群,中文聚类涵盖作业疗法、神经机制和居家康复等,英文聚类围绕虚拟现实、脑机接口和机器学习等展开;高频关键词为虚拟现实、脑机接口、机器学习和深度学习等.突现强度较高的中文关键词包括康复训练,英文关键词有深度学习;Stroke为被引频次最高的期刊,高被引期刊覆盖康复医学、神经科学、计算机科学等多学科,体现领域多学科交叉特征. 结论 DHT在脑卒中上肢运动功能康复领域的研究关注度逐年上升,研究热点主要集中在核心交互技术、神经机制和人工智能.未来人工智能与核心康复技术的跨领域整合、神经影像技术引导的靶向干预、远程居家康复系统的落地优化,以及多维度量化评估模型的构建可能为该领域的研究趋势.
Objective To analyze the current research status,hotspots and future trends of the application of digital health technolo-gy(DHT)in the rehabilitation of upper limb motor function after stroke. Methods Relevant literature on the application of DHT in upper limb motor rehabilitation for stroke patients published between January,2015 and December,2025 was retrieved from Web of Science Core Collection,CNKI and Wan-fang database.CiteSpace 6.4.R1 was used for visualized bibliometric analysis. Results A total of 1 295 publications were included,comprising 454 in Chinese and 841 in English.The annual number of publications generally showed an upward trend.China ranked first in publication output in English literature.The institutions with the highest numbers of publications were Huashan Hospital Affiliated to Fudan University and Swiss Federal Institute of Technology in Zurich.Both Chinese and English keywords formed ten clustering groups.Chinese clusters mainly involved occupational therapy,neural mechanisms and home-based rehabilita-tion,whereas English clusters focused on virtual reality,brain-computer interfaces and machine learning.High-frequency keywords included virtual reality,brain-computer interface,machine learning and deep learning.Chi-nese keywords with a strong burst included rehabilitation training,while deep learning showed a strong burst in English keywords.Stroke was the most frequently cited journal.Highly cited journals covered multiple disci-plines,including rehabilitation medicine,neuroscience and computer science,reflecting the interdisciplinary char-acteristics of this field. Conclusion Researches on DHT for upper limb motor function rehabilitation in stroke are increasing annually,focusing on core interaction technologies,neural mechanism and artificial intelligence.Future research trends may include inter-disciplinary integration of artificial intelligence with core rehabilitation technologies,neuroimaging-guided targeted interventions,optimisation of home-based rehabilitation systems,and development of multidimensional quantitative assessment models.
刘睿;高振梅;周星宇;张琦;吴建林
山东中医药大学康复医学院,山东 济南市 250355山东中医药大学中医学院,山东 济南市 250355||山东中医药大学附属医院康复理疗科,山东 济南市 250012山东中医药大学康复医学院,山东 济南市 250355山东中医药大学康复医学院,山东 济南市 250355山东中医药大学中医学院,山东 济南市 250355
医药卫生
脑卒中上肢运动功能数字健康技术文献计量学
strokeupper limb motor functiondigital health technologybibliometrics
《中国康复理论与实践》 2026 (5)
534-549,16
1.国家自然科学基金项目(No.82374311)2.山东省中医药科技项目(No.M20241805)3.山东中医药大学科学研究基金项目(No.XK2025LK03)4.山东中医药大学研究生提质创新项目(No.YJSTZCX2025078) Supported by National Natural Science Foundation of China(No.82374311),Shandong Provincial Traditional Chinese Medicine Science and Technology Project(No.M20241805),Shandong University of Traditional Chinese Medicine Scientific Research Fund(No.XK2025LK03),and Shandong University of Traditional Chinese Medicine Postgraduate Quality Enhancement and Innovation Project(No.YJSTZCX2025078)
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