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Classification of Brain Activity in Emotional States Using HOS Analysis

Author(s): Seyyed Abed Hosseini

Journal: International Journal of Image, Graphics and Signal Processing
ISSN 2074-9074

Volume: 4;
Issue: 1;
Start page: 21;
Date: 2012;
Original page

Keywords: Emotion | EEG | Higher Order Spectra | LDA

This paper proposes an emotion recognition system using EEG signals and higher order spectra. 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 states of participants, calm-neutral 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 (GA) and Support vector machine (SVM) for optimum features selection for the classifier. In this research, we achieved an average accuracy of 82.32% for the two emotional states using Linear Discriminant Analysis (LDA) classifier. We concluded that, HOS analysis could be an accurate tool in the assessment of human emotional states. We achieved to same results compared to our previous studies.
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