The Research of Depression Based on Power Spectrum

被引:1
作者
Sun, Ming-Hou [1 ]
Zhao, Qing-Lin [1 ]
Hu, Bin [1 ]
Chen, Yan [1 ]
Xu, Li-Juan [1 ]
Peng, Hong [1 ]
机构
[1] Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Gansu, Peoples R China
来源
BRAIN INFORMATICS AND HEALTH (BIH 2015) | 2015年 / 9250卷
关键词
Depression; Power spectrum; Relative power; Gravity frequency;
D O I
10.1007/978-3-319-23344-4_39
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Depression is a common emotional disease endangering human health [1], however, there is no objective and precise method for the diagnosis of depression at present both at home and overseas. Through power spectrum analysis for two leads EEG signals of the depression group and the control group, we extracted the relative power and gravity frequency, two characteristic parameters of the EEG signals each rhythm, and studied the differences between the two groups' characteristic parameters. The results of SPSS statistical analysis demonstrate that the EEG characteristic parameters have a strong correlation with the degree of depression. Specifically speaking, the relative power of depression group's left and right brain alpha rhythm is asymmetric, and the relative power of depression group's delta rhythm is higher than the control group, while the relative power of alpha rhythm is lower than the control group. In addition, the gravity frequency of depression group migrates to the low frequency compared with the control group. Relative power and gravity frequency reflect the suppressive state of the body objectively and accurately, compared with the clinical diagnosis method and the rating scale, can be more objective diagnosis of depression.
引用
收藏
页码:401 / 409
页数:9
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