2010 Second International Conference on Information Technology and Computer Science , 2010-07-24

Title : ( Higher Order Spectra Analysis of EEG Signals in Emotional Stress States )

Authors: Seyyed Abed Hosseini , Mohammad Ali Khalilzadeh , Mohammad Bagher Naghibi Sistani , Vahid Niazmand ,

Citation: BibTeX | EndNote

Abstract

This paper proposes an emotional stress recognition system with EEG signals using higher order spectra (HOS). A visual induction based acquisition protocol is designed for recording the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) under two emotional stress states of participants, Calmneutral and Negatively exited. After pre-processing the signals, higher order spectra are employed to extract the features for classifying human emotions. We used Genetic Algorithm for optimum features selection for the classifier. Using the SVM classifier, our study achieved an average accuracy of 82% for the two-abovementioned emotional stress states. We concluded that HOS analysis could be an accurate tool in the assessment of human emotional stress states. We achieved to same results compared to our previous studies.

Keywords

classification; emotional stress; EEG Signals; genetic algorithm; higher order spectra
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@inproceedings{paperid:1018335,
author = {Seyyed Abed Hosseini and Mohammad Ali Khalilzadeh and Naghibi Sistani, Mohammad Bagher and Vahid Niazmand},
title = {Higher Order Spectra Analysis of EEG Signals in Emotional Stress States},
booktitle = {2010 Second International Conference on Information Technology and Computer Science},
year = {2010},
location = {کیف},
keywords = {classification; emotional stress; EEG Signals; genetic algorithm; higher order spectra},
}

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%0 Conference Proceedings
%T Higher Order Spectra Analysis of EEG Signals in Emotional Stress States
%A Seyyed Abed Hosseini
%A Mohammad Ali Khalilzadeh
%A Naghibi Sistani, Mohammad Bagher
%A Vahid Niazmand
%J 2010 Second International Conference on Information Technology and Computer Science
%D 2010

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