EEG emotion recognition based on the dimensional models of emotions

Othman, Marini and Abdul Rahman, Abdul Wahab and Karim, Izzah and Dzulkifli, Mariam Adawiah and Taha, Imad (2013) EEG emotion recognition based on the dimensional models of emotions. Procedia - Social and Behavioral Sciences, 97. pp. 30-37. ISSN 1877-0428

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Abstract

In this paper, we propose a method for EEG emotion recognition which is tested based on 2 dimensional models of emotions, (1) the rSASM, and (2) the 12-PAC model. EEG data were collected from 5 preschoolers aged 5 years old while watching emotional faces from the Radboud Faces Database (RafD). Features were extracted using KSDE and MFCC and classified using MLP. Results show that EEG emotion recognition using the 12-PAC model gives the highest accuracy for both feature extraction methods. Results indicated that the accuracy of EEG emotion recognition is increased with the precision of the dimensional models.

Item Type:	Article (Journal)
Additional Information:	4573/34903
Uncontrolled Keywords:	brain signals; valence-arousal model; preschoolers; children; emotions; machine learning; classification. 1.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Professor Imad Taha
Date Deposited:	28 Jan 2014 12:01
Last Modified:	30 Jan 2014 08:42
URI:	http://irep.iium.edu.my/id/eprint/34903

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