Universiti Teknologi Malaysia Institutional Repository

Comparison of different methods for emotion classification

Molavi, Maziyar and Yunus, Jasmy and Akbari , Ebrahim (2012) Comparison of different methods for emotion classification. In: Proceedings - 6th Asia International Conference on Mathematical Modelling and Computer Simulation, AMS 2012. IEEE, New York, USA, pp. 50-53. ISBN 978-898867869-5

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Official URL: http://dx.doi.org/10.1109/AMS.2012.5


This article proposed emotional features clustering from electroencephalographic (EEG) signals. Facial expression images induce emotional states, which include happy, neutral and sad faces. This paper examined the effect of expression facial stimuli on event-related potential (ERPs). Moreover, It also investigated the frequency band searching by comparison between two methods; the linear support vector machine (LSVM) and the Naive Bayes classifier method. Feature extraction was performed by common spatial patterns (CSP) to reduce the dimensions of data in the frequency domain. The results showed that both methods have an ability to classify the emotional features. LSVM had more accuracy than Naive Bayes classifier. Furthermore , the gamma band was the suitable frequency interval to detect arousal emotions. Nevertheless, the happy versus sad emotional features wereclassified with higher accuracy.

Item Type:Book Section
Additional Information:Indexed by Scopus
Uncontrolled Keywords:common spatial patterns, emotion, linear support vector machine, Naive Bayes classifier
Subjects:Q Science > Q Science (General)
Divisions:Biosciences and Medical Engineering
ID Code:34551
Deposited On:09 Oct 2013 14:44
Last Modified:06 Aug 2017 08:56

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