Emotion Analysis using Different Stimuli with EEG Signals in Emotional Space

Yaşar Daşdemi̇r,Serdar Yildirim,Esen Yildirim

doi:10.28978/nesciences.328851

Yaşar Daşdemi̇r, Serdar Yildirim + Show 1 more

Open Access

https://doi.org/10.28978/nesciences.328851

Copy DOI

Abstract

Automatic detection for human-machine interfaces of the emotional states of the people is one of the difficult tasks. EEG signals that are very difficult to control by the person are also used in emotion recognition tasks. In this study, emotion analysis and classification study were conducted by using EEG signals for different types of stimuli. The combination of the audio and video information has been shown to be more effective about the classification of positive/negative (high/low) emotion by using wavelet transform from EEG signals, and true positive rate of 81.6% was obtained in valence dimension. Information of audio was found to be more effective than the information of video at classification that is made in arousal dimension, and true positive rate of 73.7% was obtained when both stimuli of audio and audio+video are used. Four class classification performance has also been examined in the space of valence-arousal.

Highlights

Emotions have a key role in communication and they are required to understand human behavior
Dimensional approach is used for the representation and the labeling of the emotions, and studies were performed about valence and arousal dimensions that are widely used in the literature
Emotion analysis and classification study are made for different types of stimuli using EEG signals

Summary

Introduction

Emotions have a key role in communication and they are required to understand human behavior. Categorical and dimensional approaches of these approaches are the most widely used models for labeling emotion in the studies about emotions recognition. Emotions are not limited to a small number of discrete emotion classes, instead of this, it is defined as points in a multi-dimensional space. In this approach, diversity of emotions is considered in 3 dimensions. Diversity of emotions is considered in 3 dimensions These dimensions are valence, arousal, and dominance. Dimensional approach is used for the representation and the labeling of the emotions, and studies were performed about valence and arousal dimensions that are widely used in the literature. Effects of emotion analysis and classification of the type of stimuli were investigated using three different stimuli types as Audio (sound), Video (visual) and Audio + Video (both sound and visual) to reveal the feelings of the participants in the database created under this study

Literature Review

Background

Material and Method

Findings

Result and Discussion