Anxiety and Depression Detection using Statistical Features

Human action is caused by the neuron activities. The distributed signals from throughout the scalp, due by these ctivities, can be recorded and analyzed subsequently. Concerning, receiving and recording brain signals can be performed by Electroencephalogram (EEG) recorder. The objective of the present study is to detect the anxiety and depression isorders using EEG signals. In order to get this purpose, some statistical features are extracted using wavelet coefficients in timefrequency domain. Experimental results using 50 subjects is achieved by 96 percent of accuracy to detect disorder