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...

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Main Authors:	Khosrowabadi , Reza, Heijnen, Michel, Abdul Rahman, Abdul Wahab, Quek, Hiok Chai
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2010
Subjects:	T57 Applied mathematics. Quantitative methods. Operation research. System analysis
Online Access:	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

id	iium-38118
recordtype	eprints
spelling	iium-381182015-01-14T20:17:18Z 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 Conference or Workshop Item 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
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T57 Applied mathematics. Quantitative methods. Operation research. System analysis
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
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.
format	Conference or Workshop Item
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
title	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_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_sort	dynamic emotion recognition system based on functional connectivity of brain regions
publisher	IEEE
publishDate	2010
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
first_indexed	2023-09-18T20:54:43Z
last_indexed	2023-09-18T20:54:43Z
_version_	1777410226994020352

The dynamic emotion recognition system based on functional connectivity of brain regions

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