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EEG affect analysis based on KDE and MFCC

Hamal, Abdul Qayoom and Othman, Marini and Yaacob, Hamwira Sakti and Abdul Rahman, Abdul Wahab (2012) EEG affect analysis based on KDE and MFCC. In: The ISCA 2nd International Conference on Advanced Computing and Communication (ISCA-ACC-2012), 27–29 June 2012, Los Angeles, California USA.

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Abstract

Classifying emotions based on the affective states of valence and arousal captured from brain discharge remains a challenge. The selection of the most efficient and reliable method of feature extraction forms a very important problem of EEG signal classification. Different methods applied are usually based upon the time-domain or frequency-domain analysis. The following study is devoted to the EEG affect analysis based on feature extraction using KDE and MFCC and comparison of results achieved. MLP is used for classification of the features extracted. The resultant feature vectors extracted using KDE provides a more accurate capture of basic emotions when compared with MFCC feature vectors.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: 4573/32132 (ISBN: 978–1–880843–87–1)
Uncontrolled Keywords: EEG, MFCC, KDE, emotions
Subjects: B Philosophy. Psychology. Religion > BF Psychology > BF511 Affection. Feeling. Emotion
T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T58.5 Information technology
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Information and Communication Technology > Department of Computer Science
Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User: Dr Hamwira Yaacob
Date Deposited: 25 Jun 2015 11:31
Last Modified: 12 May 2016 08:26
URI: http://irep.iium.edu.my/id/eprint/32132

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