关键词: 抑郁症, 小波熵, 脑电, 复杂度

Abstract: Wavelet entropy is adopted to analyze the difference of spontaneous EEG complexity between the melancholia and normal under the states of quiet and mental arithmetic tasks. It collects the 16-channel EEG data from 10 melancholia and 10 normal under the two states： a resting state with eyes closed and a mental arithmetic state with eyes closed, and then it calculates the wavelet entropy of the four group EEG data after noise reduction. The result shows that, the wavelet entropy of spontaneous EEG has a significant difference between melancholia and normal： （1）in the same state, the wavelet entropy of the melancholia’s each channel is greater than the corresponding normal’s; （2）for the same person, the wavelet entropy of each channel under the state of a resting condition with eyes closed is greater than that under the state of a mental arithmetic with eyes closed. The results show the complexity of EEG data under a resting condition with eyes closed is higher than that under a mental arithmetic with eyes closed, and the complexity of the melancholia’s EEG signal is higher than that of the healthy persons. The results are important for the diagnosis of melancholia.

Key words: melancholia, wavelet entropy, Electroencephalography（EEG）, complexity