Depression Detection Using EEG-Signals

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...

Full description

Saved in:
Bibliographic Details
Published in:International journal for research in applied science and engineering technology 2023-03, Vol.11 (3), p.645-649
Main Authors: Reddy, B. Tejaswi, Nikhitha, B. Khyathi, Reddy, L. SaiAnish, Anil, Dr. G. R.
Format: Article
Language:English
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2321-9653
2321-9653
DOI:10.22214/ijraset.2023.49505