The dynamic emotion recognition system based on functional connectivity of brain regions
Emotion perception similar to thinking, learning and remembering is consequent of complicated brain processes which are related to specific biological metabolism. Different human’s emotional states are recognizable by measuring and interpreting of human physiological signals. Bio-sensors possess a...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
IEEE
2010
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/38118/ http://irep.iium.edu.my/38118/1/The_dynamic_emotion_recognition_system_based_on_functional_connectivity_of_brain_regions.pdf |
| _version_ | 1848781541911560192 |
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| author | Khosrowabadi , Reza Heijnen, Michel Abdul Rahman, Abdul Wahab Quek, Hiok Chai |
| author_facet | Khosrowabadi , Reza Heijnen, Michel Abdul Rahman, Abdul Wahab Quek, Hiok Chai |
| author_sort | Khosrowabadi , Reza |
| building | IIUM Repository |
| collection | Online Access |
| description | Emotion perception similar to thinking, learning and remembering is consequent of complicated brain processes which are related to specific biological metabolism. Different human’s emotional states are recognizable by
measuring and interpreting of human physiological signals.
Bio-sensors possess a number of advantages against other
emotion recognition methods as they are relatively more
consistent across cultures and nations. Emotions have a
serious effect on driving. Human beings in negative and
sometimes positive emotional states can be distracted which
will increase the risk of driving. This paper presents an EEGbased emotion recognition system. Mutual information and
magnitude squared coherence are applied to investigate the
interconnectivity between 8 scalp regions. A study was
performed to collect 8 channels of EEG data from 26 healthy
right-handed subjects in experiencing 4 emotional states while exposed to audio-visual emotional stimuli. After feature extraction, 5-fold cross-validation was then performed using the KNN and SVM classifier. The results showed existence of different kind of functional brain connectivity in different emotional states. |
| first_indexed | 2025-11-14T15:51:13Z |
| format | Proceeding Paper |
| id | iium-38118 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:51:13Z |
| publishDate | 2010 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-381182020-12-16T16:06:06Z http://irep.iium.edu.my/38118/ The dynamic emotion recognition system based on functional connectivity of brain regions Khosrowabadi , Reza Heijnen, Michel Abdul Rahman, Abdul Wahab Quek, Hiok Chai T57 Applied mathematics. Quantitative methods. Operation research. System analysis Emotion perception similar to thinking, learning and remembering is consequent of complicated brain processes which are related to specific biological metabolism. Different human’s emotional states are recognizable by measuring and interpreting of human physiological signals. Bio-sensors possess a number of advantages against other emotion recognition methods as they are relatively more consistent across cultures and nations. Emotions have a serious effect on driving. Human beings in negative and sometimes positive emotional states can be distracted which will increase the risk of driving. This paper presents an EEGbased emotion recognition system. Mutual information and magnitude squared coherence are applied to investigate the interconnectivity between 8 scalp regions. A study was performed to collect 8 channels of EEG data from 26 healthy right-handed subjects in experiencing 4 emotional states while exposed to audio-visual emotional stimuli. After feature extraction, 5-fold cross-validation was then performed using the KNN and SVM classifier. The results showed existence of different kind of functional brain connectivity in different emotional states. IEEE 2010-06 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/38118/1/The_dynamic_emotion_recognition_system_based_on_functional_connectivity_of_brain_regions.pdf Khosrowabadi , Reza and Heijnen, Michel and Abdul Rahman, Abdul Wahab and Quek, Hiok Chai (2010) The dynamic emotion recognition system based on functional connectivity of brain regions. In: 2010 IEEE Intelligent Vehicles Symposium, IV 2010, 21 June 2010 - 24 June 2010, La Jolla, CA; United States. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5548102&tag=1 |
| spellingShingle | T57 Applied mathematics. Quantitative methods. Operation research. System analysis Khosrowabadi , Reza Heijnen, Michel Abdul Rahman, Abdul Wahab Quek, Hiok Chai The dynamic emotion recognition system based on functional connectivity of brain regions |
| title | The dynamic emotion recognition system based on functional connectivity of brain regions |
| title_full | The dynamic emotion recognition system based on functional connectivity of brain regions |
| title_fullStr | The dynamic emotion recognition system based on functional connectivity of brain regions |
| title_full_unstemmed | The dynamic emotion recognition system based on functional connectivity of brain regions |
| title_short | The dynamic emotion recognition system based on functional connectivity of brain regions |
| title_sort | dynamic emotion recognition system based on functional connectivity of brain regions |
| topic | T57 Applied mathematics. Quantitative methods. Operation research. System analysis |
| url | http://irep.iium.edu.my/38118/ http://irep.iium.edu.my/38118/ http://irep.iium.edu.my/38118/1/The_dynamic_emotion_recognition_system_based_on_functional_connectivity_of_brain_regions.pdf |