Specificity study of visualization analysis of electroencephalogram diagnosis of depression based on CiteSpace.
10.7507/1001-5515.202101058
- Author:
Jiaming ZHANG
1
;
Danyang LIU
1
;
Dongling ZHONG
1
;
Yuxi LI
2
;
Rongjiang JIN
1
;
Zhong ZHENG
3
;
Juan LI
1
Author Information
1. Institution of Health and Rehabilitation, Chengdu University of TCM, Chengdu 610075, P.R.China.
2. Institution of Acumox and Tuina, Chengdu University of TCM, Chengdu 610075, P.R.China.
3. Center for Neurobiological Detection, West China Hospital of Sichuan University, Chengdu 610041, P.R.China.
- Publication Type:Journal Article
- Keywords:
CiteSpace;
depressive disorder;
electroencephalogram;
visual analysis
- MeSH:
Databases, Factual;
Depression/diagnosis*;
Electroencephalography;
Humans;
Publications;
Software;
United States
- From:
Journal of Biomedical Engineering
2021;38(5):919-931
- CountryChina
- Language:Chinese
-
Abstract:
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
