EEG signals for emotion recognition

This paper proposes an emotion recognition system using the electroencephalographic (EEG) signals. Both time domain and frequency domain approaches for feature extraction were evaluated using neural network (NN) and fuzzy neural network (FNN) as classifiers. Data was collected using psychological st...

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Main Authors: Abdul Rahman, Abdul Wahab, Kamaruddin, Norhaslinda, Palaniappan, L. K., Li, M., Khosrowabadi, Reza
Format: Article
Language:English
Published: IOS, STM Publisher House 2010
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Online Access:http://irep.iium.edu.my/9549/1/EEG_signals_for_emotion_recognition.pdf
http://irep.iium.edu.my/9549/
https://iospress.metapress.com/content/b7061062m48661g6/resource-secured/?target=fulltext.pdf
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spelling my.iium.irep.95492012-02-03T00:15:25Z http://irep.iium.edu.my/9549/ EEG signals for emotion recognition Abdul Rahman, Abdul Wahab Kamaruddin, Norhaslinda Palaniappan, L. K. Li, M. Khosrowabadi, Reza T Technology (General) This paper proposes an emotion recognition system using the electroencephalographic (EEG) signals. Both time domain and frequency domain approaches for feature extraction were evaluated using neural network (NN) and fuzzy neural network (FNN) as classifiers. Data was collected using psychological stimulation experiments. Three basic emotions namely; Angry, Happy, and Sad were selected for recognition with relax as an emotionless state. Both the time domain (based on statistical method) and frequency domain (based on MFCC) approaches shows potential to be used for emotion recognition using the EEG signals. IOS, STM Publisher House 2010 Article REM application/pdf en http://irep.iium.edu.my/9549/1/EEG_signals_for_emotion_recognition.pdf Abdul Rahman, Abdul Wahab and Kamaruddin, Norhaslinda and Palaniappan, L. K. and Li, M. and Khosrowabadi, Reza (2010) EEG signals for emotion recognition. Journal of Computational Methods in Sciences and Engineering , 10 (Supp.1). pp. 1-11. ISSN 1875-8983 (O), 1472-7978 (P) https://iospress.metapress.com/content/b7061062m48661g6/resource-secured/?target=fulltext.pdf
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Abdul Rahman, Abdul Wahab
Kamaruddin, Norhaslinda
Palaniappan, L. K.
Li, M.
Khosrowabadi, Reza
EEG signals for emotion recognition
description This paper proposes an emotion recognition system using the electroencephalographic (EEG) signals. Both time domain and frequency domain approaches for feature extraction were evaluated using neural network (NN) and fuzzy neural network (FNN) as classifiers. Data was collected using psychological stimulation experiments. Three basic emotions namely; Angry, Happy, and Sad were selected for recognition with relax as an emotionless state. Both the time domain (based on statistical method) and frequency domain (based on MFCC) approaches shows potential to be used for emotion recognition using the EEG signals.
format Article
author Abdul Rahman, Abdul Wahab
Kamaruddin, Norhaslinda
Palaniappan, L. K.
Li, M.
Khosrowabadi, Reza
author_facet Abdul Rahman, Abdul Wahab
Kamaruddin, Norhaslinda
Palaniappan, L. K.
Li, M.
Khosrowabadi, Reza
author_sort Abdul Rahman, Abdul Wahab
title EEG signals for emotion recognition
title_short EEG signals for emotion recognition
title_full EEG signals for emotion recognition
title_fullStr EEG signals for emotion recognition
title_full_unstemmed EEG signals for emotion recognition
title_sort eeg signals for emotion recognition
publisher IOS, STM Publisher House
publishDate 2010
url http://irep.iium.edu.my/9549/1/EEG_signals_for_emotion_recognition.pdf
http://irep.iium.edu.my/9549/
https://iospress.metapress.com/content/b7061062m48661g6/resource-secured/?target=fulltext.pdf
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score 13.19449