基于Pubmed数据库文献挖掘的近5年脑机交互研究热点的聚类分析

Bibliometric and hotspot analysis of brain-machine interfaces based on pubmed database with literature mining in past five years

目的:调查有关脑机交互(brain-machine Interfaces,BCI)研究的医学文献,得出近期脑机交互研究热点。方法:应用美国国立医学图书馆开发的Pubmed数据库进行近5年有关脑机交互的文献检索,应用书目共现分析系统(bibliographic Item CO-Occurrence Matrix Builder,BICOMB)进行文献计量分析,SPSS 19.0软件进行聚类分析。结果:通过对脑机交互高频关键词聚类分析绘制树状图,总结得出了3大类研究热点:1)非侵入式的脑机交互信号获取和解码;2)侵入式获取信号的脑机交互研究;3)脑机交互在脑卒中康复中的研究。结论:脑机交互技术目前正在快速发展,但仍需更方便、有效、安全的信号提取及转化技术,以求积极应用于临床治疗。

Objective：To analyze the published articles of brain-machine interfaces and get the recent research hotspot. Methods：Searching brain-machine interfaces literatures through PubMed database of US Congress Library of Medicine in past ifve years, using BICOMB to bibliometric analysis and SPSS 19.0 to cluster analysis. Results：hTree research hotspots were concluded by analyzing the key words：1） non-invasive brain signal acquisition and decoding of brain-machine Interfaces;2） invasive brain signal acquisition of brain-machine Interfaces;3） brain-computer interaction research in stroke rehabilitation. Conclusion：Researches on BCI developed rapidly, but signal acquisition and decoding need more convenient, effective and safer in the future studies and useful clinical practice for BCI is the ifrst priority.