A Novel Emotion Elicitation Index Using Frontal Brain Asymmetry for Enhanced EEG-Based Emotion Recognition

Authors:
P. C. Petrantonakis;L. J. Hadjileontiadis
Affiliations:
Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece;-
Venue:
IEEE Transactions on Information Technology in Biomedicine
Year:
2011

Citing 0
Cited 2

EEG-based emotion estimation using Bayesian weighted-log-posterior function and perceptron convergence algorithm

Computers in Biology and Medicine
Emotional state classification from EEG data using machine learning approach

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper aims at providing a novel method for evaluating the emotion elicitation procedures in an electroencephalogram (EEG)-based emotion recognition setup. By employing the frontal brain asymmetry theory, an index, namely asymmetry Index (AsI), is introduced, in order to evaluate this asymmetry. This is accomplished by a multidimensional directed information analysis between different EEG sites from the two opposite brain hemispheres. The proposed approach was applied to three-channel (Fp1, Fp2, and F3/F4 10/20 sites) EEG recordings drawn from 16 healthy right-handed subjects. For the evaluation of the efficiency of the AsI, an extensive classification process was conducted using two feature-vector extraction techniques and a SVM classifier for six different classification scenarios in the valence/arousal space. This resulted in classification results up to 62.58% for the user independent case and 94.40% for the user-dependent one, confirming the efficacy of AsI as an index for the emotion elicitation evaluation.