Open AccessEEG based mental state analysis
Author(s) -
Krishnapriya Ajith,
R. Menaka,
Shani S. Kumar
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1911/1/012014
Subject(s) - electroencephalography , convolutional neural network , computer science , affect (linguistics) , mental state , emotion recognition , artificial intelligence , cognition , deep learning , cognitive psychology , pattern recognition (psychology) , psychology , neuroscience , communication
This work proposes a method for mental state analysis from the Electroencephalogram (EEG) signal data using Convolutional Neural Network (CNN). In recent years, deep learning techniques, particularly CNN have become a very popular topic. Emotions also play a very crucial role in our daily life. Emotions affect a person’s cognition, behaviour and decision-making. In this paper, we analyse the EEG signals and classify them into various emotions. The result would be a real-time EEG-based emotion recognition system. The DEAP dataset, which is a multimodal dataset, has been used in this study for analysis of human mental states.