@article{ref1,
title="Research progress in electroencephalography of depression",
journal="Chinese Journal of Biomedical Engineering",
year="2020",
author="Xiaoya, L. and Shuang, L. and Dongyue, G. and Xingwei, A. and Jiajia, Y. and Dong, M.",
volume="39",
number="3",
pages="351-361",
abstract="Depression is an affective disease with significant and prolonged mood depression as the main symptoms, having a high incidence and spreading across all age groups. With the rapid development of the world economy and the ever-increasing competition in social life, the incidence of global depression has also rapidly risen. At the same time, diseased and suicide has showed a trend of younger age. Therefore, attention must be paid to the prevention and treatment of depression. Currently, diagnosis and treatment of depression mainly depend on subjective scale evaluation and doctor's experience, with poor consistency, while high misdiagnosis rate and missed diagnosis rate, not objective and effective enough, and lacking of convenient and rapid quantitative diagnostic indicators and methods. Electroencephalography (EEG) is a non-invasive measure to detect changes in cerebral cortical neural activity, which has high time resolution and rich information on central neurocognitive and physiological activities. And it is an objective and effective method to obtain brain pathological changes in depression. In recent years, the specificity of EEG for depression has achieved progress. This paper comprehensively reviewed the progress of EEG rhythm, nonlinear dynamic parameters, event-related potentials (ERPs) response and specificity of brain neural network research, existing problems, solutions for these problems, and discussed future visions, in order to promote the diagnosis and treatment of depression and to develop more effective anti-depression techniques. © 2020 Chinese Academy of Medical Sciences. All rights reserved.<p /><p>Language: zh</p>",
language="zh",
issn="0258-8021",
doi="10.3969/j.issn.0258-8021.2020.03.13",
url="http://dx.doi.org/10.3969/j.issn.0258-8021.2020.03.13"
}