Depression Detection Using EEG-Signals

Abstract

Abstract: The most severe kind of mood disorder, depression, has a significant impact on mental health and causes difficulties in daily living. Electroencephalogram (EEG) signals can detect this mood condition. EEG signal analysis is a tedious, timeconsuming, and highly specialized method for manually diagnos- ing depression. Therefore, a fully automated depression detection system developed using EEG signals will be useful to clinicians. In this research work, a CNN based hybrid model was designed and this model resulted with 90percent accuracy, whereas with SVM it resulted in 60.