《中国康复理论与实践》 ›› 2025, Vol. 31 ›› Issue (11): 1279-1289.doi: 10.3969/j.issn.1006-9771.2025.11.005
蒋逸1, 梁康1, 楚家豪2, 杨丹3, 高飞4, 厉含之4, 杜晓霞4(
)
收稿日期:2025-09-12
修回日期:2025-10-10
出版日期:2025-11-25
发布日期:2025-11-26
通讯作者:
杜晓霞
E-mail:duxiaoxia2005@gmail.com
作者简介:蒋逸(1998-),男,汉族,浙江衢州市人,硕士研究生,主要研究方向:神经康复。
基金资助:
JIANG Yi1, LIANG Kang1, CHU Jiahao2, YANG Dan3, GAO Fei4, LI Hanzhi4, DU Xiaoxia4(
)
Received:2025-09-12
Revised:2025-10-10
Published:2025-11-25
Online:2025-11-26
Contact:
DU Xiaoxia
E-mail:duxiaoxia2005@gmail.com
Supported by:摘要:
目的 分析近5年脑机接口技术(BCI)在脑卒中康复领域的应用趋势和研究热点。
方法 检索2021年1月至2025年8月在Web of Science核心合集数据库中BCI在脑卒中康复领域研究的相关文献,采用CiteSpace 6.4.R1软件进行可视化分析。
结果 共纳入458篇文献。年发文量持续保持高水平,发文量最多的国家是中国,发文量最多的机构是复旦大学和Aalborg University,发文量最多的作者是Mads R Jochumsen,被引频次最多的作者是Pfurtscheller G。brain-computer interface、motor imagery、upper limb和deep learning是领域内的高频关键词和突现词。
结论 近5年BCI在脑卒中康复领域研究总体发文量保持在高水平,研究热点聚焦于BCI算法技术革新,以及通过多维度进行神经机制的验证和康复效果评估。
中图分类号:
蒋逸, 梁康, 楚家豪, 杨丹, 高飞, 厉含之, 杜晓霞. 2021年至2025年脑机接口技术在脑卒中康复领域应用的文献计量分析[J]. 《中国康复理论与实践》, 2025, 31(11): 1279-1289.
JIANG Yi, LIANG Kang, CHU Jiahao, YANG Dan, GAO Fei, LI Hanzhi, DU Xiaoxia. Application of brain-computer interface technology in stroke rehabilitation from 2021 to 2025: a bibliometric analysis[J]. Chinese Journal of Rehabilitation Theory and Practice, 2025, 31(11): 1279-1289.
表6
关键词聚类表"
| 聚类号 | 节点数/n | 轮廓值 | 主要关键词 |
|---|---|---|---|
| #0 | 21 | 0.911 | machine learning; brain asymmetry; action observation; artificial intelligence |
| #1 | 19 | 0.923 | amyotrophic lateral sclerosis; heart rate variability; human; sensorimotor rhythms |
| #2 | 17 | 0.916 | feature extraction; stroke (medical condition); motors; convolutional neural networks |
| #3 | 16 | 0.823 | motor imagery; brain-computer interface; stroke rehabilitation; electroencephalography (EEG) |
| #4 | 16 | 0.950 | functional near-infrared spectroscopy; effective connectivity; clinical translation |
| #5 | 15 | 0.913 | motor imagery; brain-computer interface (BCI) ; brain-computer interface; stroke |
| #6 | 15 | 0.950 | EEG; hemiparesis; systematic review; decoding; brain-computer interfaces |
| #7 | 15 | 0.899 | neurofeedback, motor restoration, bimanual BCI-FES, delta alpha ratio |
| #8 | 13 | 0.871 | electroencephalography (EEG), upper limb, brain-computer interface |
| #9 | 12 | 0.922 | motor rehabilitation, functional electrical stimulation, continuous trajectory reconstruction |
| #10 | 12 | 0.831 | neurological diseases, virtual reality, neuroscience, volitional control |
| #11 | 11 | 0.968 | motor function, upper extremity, stroke, network calibration, robotic arm |
| #12 | 9 | 0.989 | movement-related cortical potential, kinesthetic motor imagery, event-related desynchronization |
| #13 | 8 | 0.805 | neuroprosthetic, gps tracking, community participation, intracortical brain-computer interfaces |
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