EEG signals for emotion recognition

Issue title: Special Supplement Issue in Section A and B: Selected Papers from the ISCA International Conference on Software Engineering and Data Engineering, 2009

Article type: Research Article

Authors: Wahab, A.^{; *} | Kamaruddin, N. | Palaniappan, L.K. | Li, M. | Khosrowabadi, R.

Affiliations: Kulliyah of Information and Communication Technology, International Islamic University Malaysia, Jalan Gombak, Kuala Lumpur, Malaysia

Correspondence: [*] Corresponding author: Dr. Abdul Wahab, Kulliyah of Information and Communication Technology, International Islamic University Malaysia, Jalan Gombak, 51300, Kuala Lumpur, Malaysia. Tel.: +60 3 6196 5179/60 6196 5662; E-mail: [email protected].

Abstract: This paper proposes an emotion recognition system using the electroencephalographic (EEG) signals. Both time domain and frequency domain approaches for feature extraction were evaluated using neural network (NN) and fuzzy neural network (FNN) as classifiers. Data was collected using psychological stimulation experiments. Three basic emotions namely; Angry, Happy, and Sad were selected for recognition with relax as an emotionless state. Both the time domain (based on statistical method) and frequency domain (based on MFCC) approaches shows potential to be used for emotion recognition using the EEG signals.

Keywords: Emotion, EEG, RVM, time domain, EFuNN, MFCC

DOI: 10.3233/JCM-2010-0263

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 10, no. s1, pp. S1-S11, 2010