EEG emotion recognition system
This chapter proposes an emotion recognition system based on time domain analysis of the bio-signals for emotion features extraction. Three different types of emotions (happy, relax and sad) are classified and results are compared using five different algorithms based on RVM, MLP, DT, SVM and Bayesi...
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| Language: | English |
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Springer US
2009
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| Online Access: | http://irep.iium.edu.my/38152/1/EEG_Emotion_Recognition_System.pdf http://irep.iium.edu.my/38152/ http://link.springer.com/chapter/10.1007%2F978-0-387-79582-9_10 |
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my.iium.irep.381522020-06-12T07:52:15Z http://irep.iium.edu.my/38152/ EEG emotion recognition system Ma, Li Ya Quek, Chai Teo, Kaixiang Abdul Rahman, Abdul Wahab Abut, Huseyin T Technology (General) This chapter proposes an emotion recognition system based on time domain analysis of the bio-signals for emotion features extraction. Three different types of emotions (happy, relax and sad) are classified and results are compared using five different algorithms based on RVM, MLP, DT, SVM and Bayesian techniques. Experimental results show the potential of using the time domain analysis for real-time application. Springer US 2009-06 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/38152/1/EEG_Emotion_Recognition_System.pdf Ma, Li Ya and Quek, Chai and Teo, Kaixiang and Abdul Rahman, Abdul Wahab and Abut, Huseyin (2009) EEG emotion recognition system. In: In-vehicle corpus and signal processing for driver behavior. Springer US, Spring Street, USA, pp. 125-135. ISBN 978-0-387-79581-2 (P), 978-0-387-79582-9 (O) http://link.springer.com/chapter/10.1007%2F978-0-387-79582-9_10 10.1007/978-0-387-79582-9_10 |
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Malaysia |
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International Islamic University Malaysia |
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| language |
English |
| topic |
T Technology (General) |
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T Technology (General) Ma, Li Ya Quek, Chai Teo, Kaixiang Abdul Rahman, Abdul Wahab Abut, Huseyin EEG emotion recognition system |
| description |
This chapter proposes an emotion recognition system based on time domain analysis of the bio-signals for emotion features extraction. Three different types of emotions (happy, relax and sad) are classified and results are compared using five different algorithms based on RVM, MLP, DT, SVM and Bayesian techniques. Experimental results show the potential of using the time domain analysis for real-time application. |
| format |
Book Chapter |
| author |
Ma, Li Ya Quek, Chai Teo, Kaixiang Abdul Rahman, Abdul Wahab Abut, Huseyin |
| author_facet |
Ma, Li Ya Quek, Chai Teo, Kaixiang Abdul Rahman, Abdul Wahab Abut, Huseyin |
| author_sort |
Ma, Li Ya |
| title |
EEG emotion recognition system |
| title_short |
EEG emotion recognition system |
| title_full |
EEG emotion recognition system |
| title_fullStr |
EEG emotion recognition system |
| title_full_unstemmed |
EEG emotion recognition system |
| title_sort |
eeg emotion recognition system |
| publisher |
Springer US |
| publishDate |
2009 |
| url |
http://irep.iium.edu.my/38152/1/EEG_Emotion_Recognition_System.pdf http://irep.iium.edu.my/38152/ http://link.springer.com/chapter/10.1007%2F978-0-387-79582-9_10 |
| _version_ |
1672610101308948480 |