The invention discloses a method for extracting electroencephalogram (EEG) characteristic based on a quantitative EEG. The method comprises the following steps of synchronous acquiring 16-lead EEG signal potential data by using a personal computer (PC) and an electroencephalograph visual interface program and displaying EEG waveform acquired in real time; preprocessing the acquired EEG signals to remove power frequency interference, noise signals, electro-oculogram interference and myoelectric interference; respectively extracting power coupling coefficient based on absolute power and relative power of 5 frequency bands of the 16-lead EEG signals and asymmetry coefficient based on the density of high and low frequency band power spectrum; and classifying the EEG signals in the quiescent state by using a support vector machine (SVM) fusion network with a double-layer structure. By the method, the EEG signals of PSD patients and normal people can be distinguished, high classification accurate rate is achieved, the depression degree of the PSD patients can be effectively recognized, basis is provided for research on the objective diagnosis standard of PSD, and important social significance is achieved.