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
| 作者: |
1金磊,
2胡柯嘉
1 苏州大学附属无锡市第九人民医院骨科，江苏 无锡 214062 2 复旦大学附属华山医院显微外科，上海 200040 |
| 通讯: |
胡柯嘉
Email: doc_kejiahu@126.com |
| DOI: | 10.3978/j.issn.2095-6959.2015.09.009 |
| 基金: | 国家863计划课题, SS2015AA020501 |
摘要
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。
关键词：
脑机交互
文献计量学
聚类分析
研究热点
脑卒中康复
Bibliometric and hotspot analysis of brain-machine interfaces based on pubmed database with literature mining in past five years
CorrespondingAuthor: HU Kejia Email: doc_kejiahu@126.com
DOI: 10.3978/j.issn.2095-6959.2015.09.009
Abstract
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 five years, using BICOMB to bibliometric analysis and SPSS 19.0 to cluster analysis. Results: Three 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 first priority.