EEG emotion recognition based on the dimensional models of emotions
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). Fea...
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iium-349032014-01-30T00:42:36Z http://irep.iium.edu.my/34903/ EEG emotion recognition based on the dimensional models of emotions Othman, Marini Abdul Rahman, Abdul Wahab Karim, Izzah Dzulkifli, Mariam Adawiah Taha, Imad QA75 Electronic computers. Computer science 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. Elsevier 2013 Article PeerReviewed application/pdf en http://irep.iium.edu.my/34903/1/EEG_emotion_recognition_based_on_the_dimensional_models_of.pdf 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 http://dx.doi.org/10.1016/j.sbspro.2013.10.201 doi:10.1016/j.sbspro.2013.10.201 |
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topic |
QA75 Electronic computers. Computer science |
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QA75 Electronic computers. Computer science Othman, Marini Abdul Rahman, Abdul Wahab Karim, Izzah Dzulkifli, Mariam Adawiah Taha, Imad EEG emotion recognition based on the dimensional models of emotions |
description |
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. |
format |
Article |
author |
Othman, Marini Abdul Rahman, Abdul Wahab Karim, Izzah Dzulkifli, Mariam Adawiah Taha, Imad |
author_facet |
Othman, Marini Abdul Rahman, Abdul Wahab Karim, Izzah Dzulkifli, Mariam Adawiah Taha, Imad |
author_sort |
Othman, Marini |
title |
EEG emotion recognition based on the dimensional models of emotions |
title_short |
EEG emotion recognition based on the dimensional models of emotions |
title_full |
EEG emotion recognition based on the dimensional models of emotions |
title_fullStr |
EEG emotion recognition based on the dimensional models of emotions |
title_full_unstemmed |
EEG emotion recognition based on the dimensional models of emotions |
title_sort |
eeg emotion recognition based on the dimensional models of emotions |
publisher |
Elsevier |
publishDate |
2013 |
url |
http://irep.iium.edu.my/34903/ http://irep.iium.edu.my/34903/ http://irep.iium.edu.my/34903/ http://irep.iium.edu.my/34903/1/EEG_emotion_recognition_based_on_the_dimensional_models_of.pdf |
first_indexed |
2023-09-18T20:50:11Z |
last_indexed |
2023-09-18T20:50:11Z |
_version_ |
1777409941877817344 |