中国康复理论与实践2026，Vol.32Issue(3)：304-316,13.DOI:10.3969/j.issn.1006-9771.2026.03.007
重复外周磁刺激在康复治疗中应用的文献计量分析
Application of repetitive peripheral magnetic stimulation in rehabilitation therapy:a bibliometric analysis
摘要
Abstract
Objective To analyze the development status and research frontiers of repetitive peripheral magnetic stimulation(rPMS)in rehabilitation therapy. Methods Relevant literatures on rPMS in rehabilitation therapy were retrieved from CNKI,Wanfang data,VIP and Web of Science Core Collection from January,2005 to December,2024.CiteSpace 6.4.R1 and VOSviewer 1.6.20 were used for visualization analysis. Results A total of 202 publications were included,81 in Chinese and 121 in English,with an overall increasing trend in annual publications.Japan had the highest number of English publications,while Germany demonstrated the highest centrality.The most productive institution in Chinese publications was Huashan Hospital Affiliated to Fu-dan University,with the most prolific authors being Xu Liang,Cai Qian and Ma Ming.For English publications,Technical University of Munich was the most productive institution,Schneider Cyril was the most productive au-thor,and Clinical Neurophysiology was the most influential journal.Hotspot keywords in both Chinese and Eng-lish publications included stroke,spasticity,repetitive transcranial magnetic stimulation,dysphagia,motor func-tion,pain and plasticity,etc.The most bursting words in Chinese and English publications were spasticity and pain,respectively. Conclusion Researches on rPMS in rehabilitation therapy show steady growth,primarily focusing on functional rehabili-tation for neurological diseases such as stroke and cerebral palsy,as well as the treatment of painful diseases in-cluding low back pain.关键词
重复外周磁刺激/康复/文献计量学Key words
repetitive peripheral magnetic stimulation/rehabilitation/bibliometrics分类
医药卫生引用本文复制引用
蒲心语,王靖萱,王虎军,修安达,王颖鹏..重复外周磁刺激在康复治疗中应用的文献计量分析[J].中国康复理论与实践,2026,32(3):304-316,13.基金项目
科学技术部"人工智能(AI)辅助系统化、标准化、分层级物理刺激负荷强度检测体系构建"项目(No.2022YFC3600501) Ministry of Science and Technology the Construction of an AI-assisted Systematic,Standardized,and Hierarchical Physical Stimulation Load Intensity Detection System(No.2022YFC3600501) （AI）
