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

doi:10.3969/j.issn.1006-9771.2026.05.004

Abstract

Abstract:

Objective To analyze the current research status, hotspots and future trends of the application of digital health technology (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 Wanfang 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 rehabilitation, 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. Chinese 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 disciplines, including rehabilitation medicine, neuroscience and computer science, reflecting the interdisciplinary characteristics 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.

Key words: stroke, upper limb motor function, digital health technology, bibliometrics

CLC Number:

R743.3

LIU Rui, GAO Zhenmei, ZHOU Xingyu, ZHANG Qi, WU Jianlin. Application of digital health technologies in upper limb motor function rehabilitation after stroke from 2015 to 2025: a bibliometric analysis[J]. Chinese Journal of Rehabilitation Theory and Practice, 2026, 32(5): 534-549.

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国家	发文量/n	中心性
中国	220	0.12
美国	158	0.43
意大利	85	0.13
韩国	67	0.00
加拿大	55	0.20

排名	中文文献		英文文献
排名	机构	发文量/n	机构	发文量/n
1	复旦大学附属华山医院	19	ETH Zurich	23
2	中国康复研究中心北京博爱医院	8	Hong Kong Polytechnic University	18
3	上海体育大学	7	University of Wisconsin System	16
4	首都医科大学康复医学院	6	McGill University	14
5	首都医科大学宣武医院康复医学科	5	IRCCS Santa Lucia	12

排名	期刊	被引频次	中心性
1	Stroke	676	0.70
2	Neurorehabilitation and Neural Repair	659	0.71
3	Journal of NeuroEngineering and Rehabilitation	639	0.62
4	Archives of Physical Medicine and Rehabilitation	630	0.28
5	Physical Therapy	413	0.34

Application of digital health technologies in upper limb motor function rehabilitation after stroke from 2015 to 2025: a bibliometric analysis

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排名	中文文献		英文文献
排名	关键词	频次	关键词	频次
1	脑卒中	365	upper limb	272
2	上肢运动功能	156	virtual reality	241
3	偏瘫	78	brain-computer interface	116
4	康复训练	74	stroke rehabilitation	88
5	脑机接口	60	machine learning	62
6	虚拟现实	58	motor function	30
7	手功能	30	motor imagery	30
8	运动想象	26	motor recovery	28
9	上肢康复机器人	23	stroke	26
10	镜像疗法	19	deep learning	25

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