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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 31-439
Full Name: Mohd Rizon Mohamed Juhari
Position: Associate Professor
Age: ON
Sex: Male
Address: Universiti Malaysia Perlis
Country: MALAYSIA
Tel: +6019-3740755
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Fax: +604-9798142
E-mail address: rizonkun@hotmail.com
Other E-mails: rizonkun@hotmail.com
Title of the Paper: Asymmetric ratio and FCM based salient channel selection for human emotion detection using EEG
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Number of paper pages: 10
Abstract: Electroencephalogram (EEG) is one of the most reliable physiological signals used for detecting the emotional states of human brain. We propose Asymmetric Ratio (AR) based channel selection for human emotion recognition using EEG. Selection of channels reduces the feature size, computational load requirements and robustness of emotions classification. We address this crisis using Asymmetric Variance Ratio (AVR) and Amplitude Asymmetric Ratio (AAR) as new channel selection methods. Using these methods the 28 homogeneous pairs of EEG channels is reduced to 4 and 2 channel pairs respectively. These methods significantly reduce the number of homogeneous pair of channels to be used for emotion detection. This approach is illustrated with 5 distinct emotions (disgust, happy, surprise, sad, and fear) on 63 channels EEG data recorded from 5 healthy subjects. In this study, we used Multi-Resolution Analysis (MRA) based feature extraction the original and reduced set of cha!
nnels for emotion classification. These approaches were empirically evaluated by using a simple unsupervised classifier, Fuzzy C-Means clustering with variable clusters. The paper concludes by discussing the impact of reduced channels on emotion recognition with larger number of channels and outlining the potential of the new channel selection method.
Keywords: EEG, Human Emotions, Asymmetric Ratios, Channel selection, Wavelet Transform, Fuzzy C-Means (FCM) clustering.
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