Zhang Jiaming, Liu Danyang, Zhong Dongling, Li Yuxi, Jin Rongjiang, Zheng Zhong, Li Juan
Institution of Health and Rehabilitation, Chengdu University of TCM, Chengdu 610075, P.R.China.
Institution of Acumox and Tuina, Chengdu University of TCM, Chengdu 610075, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2021 Oct 25;38(5):919-931. doi: 10.7507/1001-5515.202101058.
This paper analyzed literatures on the specificity study of electroencephalogram (EEG) in the diagnosis of depression since 2010 to 2020, summarized the recent research directions in this field and prospected the future research hotspots at home and abroad. Based on databases of China National Knowledge Infrastructure (CNKI) and the core collection of Web of Science (WOS), CiteSpace software was used to analyze the relevant literatures in this research field. The number of relevant literatures, countries, authors, research institutions, key words, cited literatures and periodicals related to this research were analyzed, respectively, to explore research hotspots and development trends in this field. A total of 2 155 articles were included in the WOS database. The most published institution was the University of Toronto, the most published country was the United States, China occupied the third place, and the hot keywords were anxiety, disorder, brain and so on. A total of 529 literatures were included and analyzed in CNKI database. The institution with the most publications was the Mental Health Center of West China Hospital of Sichuan University, and the hot keywords were EEG signal, event-related potential, convolutional neural network, schizophrenia, etc This study finds that EEG study of depression is developing rapidly at home and abroad. Research directions in the world mainly focus on exploring the characteristics of spontaneous EEG rhythm and nonlinear dynamic parameters during sleep in depressed patients. In addition, synchronous transcranial magnetic stimulation (TMS) and EEG technologies also attract much attention abroad, and the future research hotspot will be on the mechanism of EEG on patients with major depression. Domestic research directions mainly focus on the classification of resting EEG and the control study of resting EEG power spectrum entropy in patients with schizophrenia and depression, and future research hotspot is the basic and clinical EEG study of depressed patients complicated with anxiety.
本文分析了2010年至2020年期间关于脑电图(EEG)在抑郁症诊断中特异性研究的文献,总结了该领域近期的研究方向,并对国内外未来的研究热点进行了展望。基于中国知网(CNKI)数据库和科学引文索引(SCI)核心合集,运用CiteSpace软件对该研究领域的相关文献进行分析。分别分析了与本研究相关的文献数量、国家、作者、研究机构、关键词、被引文献和期刊,以探索该领域的研究热点和发展趋势。SCI数据库共纳入2155篇文章。发文量最多的机构是多伦多大学,发文量最多的国家是美国,中国位居第三,热门关键词有焦虑、障碍、大脑等。CNKI数据库共纳入并分析了529篇文献。发文量最多的机构是四川大学华西医院心理卫生中心,热门关键词有脑电信号、事件相关电位、卷积神经网络、精神分裂症等。本研究发现,国内外关于抑郁症的脑电图研究发展迅速。国外的研究方向主要集中在探索抑郁症患者睡眠期间自发脑电节律和非线性动力学参数的特征。此外,同步经颅磁刺激(TMS)和脑电图技术在国外也备受关注,未来的研究热点将是脑电图对重度抑郁症患者的作用机制。国内的研究方向主要集中在静息脑电图的分类以及精神分裂症和抑郁症患者静息脑电图功率谱熵的对照研究,未来的研究热点是伴有焦虑的抑郁症患者的脑电图基础与临床研究。