Electroencephalography Symmetry in Power, Waveform and Power Spectrum in Major Depression

脑电图 光谱密度 波形 萧条(经济学) 对称(几何) 模式识别(心理学) 熵(时间箭头) 人工智能 心理学 样本熵 相关性 计算机科学 听力学 数学 统计 物理 神经科学 医学 电信 宏观经济学 经济 量子力学 雷达 几何学
作者
Ziyi Lin,Juntao Liu,Feng Duan,Rui Liu,Shengwei Xu,Xinxia Cai
标识
DOI:10.1109/embc44109.2020.9176462
摘要

Depression is a harmful disease with high incidence. However, no effective method based on physiological information detection has been published to diagnose depression. Electroencephalography (EEG) has been used as a tool to detect physiological information of depressed patients and the symmetry of EEG receives much attention. This research focused on the symmetry of EEG in left and right homologous brain regions. 22 healthy volunteers and 41 volunteers of major depression were tested and three methods, average power ratio, waveform correlation and power spectral correlation, were adopted to measure the symmetry in all frequency bands and all brain regions. After t-test, homologous site pairs in particular frequency bands with significant differences between major depressed patients and controls were found out. Then sample entropy analysis was adopted, trying to figure out further connections between EEG symmetry and major depression. The accuracy tests were also taken and the average accuracy of some tests could reach 93.7%. The result of this research can hopefully serve as a theoretical basis for pattern recognition in the diagnosis of depression. The accuracy of pattern recognition based on multiple processing methods and sites will increase dramatically.
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