Abstract

Depression is one of the deadliest ailments hitting about a noteworthy populace around the world This work proposes a method to identify Depression in subject by using EEG database recorded on different people of different age groups and social organizations. by asking PHQ-9 score is computed for each subject. EEG frequency bands values are tabulated by using Bluetooth based Neurosky's Mindwave kit. In this work focus is to identify depression by Support Vector Machine (SVM). 47 Samples are set up by making inquiries from standard poll with a Wright and wrong replies in a diverse era from the individual in wearable head unit. 39 samples are trained and 8 are tested. In this work SVM classifier’s confusion matrix is derived by MATLAB program and accuracy of 75 % is achieved.