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...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOS, STM Publisher House
2010
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/9549/ http://irep.iium.edu.my/9549/1/EEG_signals_for_emotion_recognition.pdf |
| _version_ | 1848777136963321856 |
|---|---|
| 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 |
| building | IIUM Repository |
| collection | Online Access |
| 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.
|
| first_indexed | 2025-11-14T14:41:12Z |
| format | Article |
| id | iium-9549 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T14:41:12Z |
| publishDate | 2010 |
| publisher | IOS, STM Publisher House |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-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 PeerReviewed 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 |
| spellingShingle | T Technology (General) Abdul Rahman, Abdul Wahab Kamaruddin, Norhaslinda Palaniappan, L. K. Li, M. Khosrowabadi, Reza EEG signals for emotion recognition |
| title | 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_short | EEG signals for emotion recognition |
| title_sort | eeg signals for emotion recognition |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/9549/ http://irep.iium.edu.my/9549/ http://irep.iium.edu.my/9549/1/EEG_signals_for_emotion_recognition.pdf |