Affective computing model using source-temporal domain

This paper proposes a new Electroencephalographic (EEG) emotion recognition system (EEG-ER) that captures human emotion dynamics. EEG signals are collected from ten healthy subjects, aged 5-6 years. Four basic emotions namely; happy, sad, neutral and fear were induced from the participants using a...

Full description

Bibliographic Details
Main Authors:	Shams, Wafaa Khazaal, Abdul Rahman, Abdul Wahab, Alshaikhli, Imad Fakhri Taha
Format:	Article
Language:	English
Published:	Elsevier 2013
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/34639/ http://irep.iium.edu.my/34639/ http://irep.iium.edu.my/34639/ http://irep.iium.edu.my/34639/1/Affective_computing_model_using_source-temporal_domain.pdf

id	iium-34639
recordtype	eprints
spelling	iium-346392018-05-24T07:44:45Z http://irep.iium.edu.my/34639/ Affective computing model using source-temporal domain Shams, Wafaa Khazaal Abdul Rahman, Abdul Wahab Alshaikhli, Imad Fakhri Taha QA75 Electronic computers. Computer science This paper proposes a new Electroencephalographic (EEG) emotion recognition system (EEG-ER) that captures human emotion dynamics. EEG signals are collected from ten healthy subjects, aged 5-6 years. Four basic emotions namely; happy, sad, neutral and fear were induced from the participants using affective photographs of varying arousal from the Radbound faces database (RaFD). The affective space model proposed by Russell (1980) was used for classifying the acquired signals into a 2-dimensional structure of valence and arousal. Feature extraction method utilized was Time Difference of Arrival (TDOA) approach for reconstructing the relative source domain of brain activity. Regularized Least Square (RLS) and Multi-Layer Perception (MLP) neural network was used for classification process. The results were compared with wavelet coefficients (WC) method and showed high accuracy around 96% for user independent classification and approximately100% for user dependent classification. Overall the results reflect significant stability of accuracy rate among subjects using the proposed method. Elsevier 2013 Article PeerReviewed application/pdf en http://irep.iium.edu.my/34639/1/Affective_computing_model_using_source-temporal_domain.pdf Shams, Wafaa Khazaal and Abdul Rahman, Abdul Wahab and Alshaikhli, Imad Fakhri Taha (2013) Affective computing model using source-temporal domain. Procedia - Social and Behavioral Sciences, 97. pp. 54-62. ISSN 1877-0428 http://dx.doi.org/10.1016/j.sbspro.2013.10.204 10.1016/j.sbspro.2013.10.204
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Shams, Wafaa Khazaal Abdul Rahman, Abdul Wahab Alshaikhli, Imad Fakhri Taha Affective computing model using source-temporal domain
description	This paper proposes a new Electroencephalographic (EEG) emotion recognition system (EEG-ER) that captures human emotion dynamics. EEG signals are collected from ten healthy subjects, aged 5-6 years. Four basic emotions namely; happy, sad, neutral and fear were induced from the participants using affective photographs of varying arousal from the Radbound faces database (RaFD). The affective space model proposed by Russell (1980) was used for classifying the acquired signals into a 2-dimensional structure of valence and arousal. Feature extraction method utilized was Time Difference of Arrival (TDOA) approach for reconstructing the relative source domain of brain activity. Regularized Least Square (RLS) and Multi-Layer Perception (MLP) neural network was used for classification process. The results were compared with wavelet coefficients (WC) method and showed high accuracy around 96% for user independent classification and approximately100% for user dependent classification. Overall the results reflect significant stability of accuracy rate among subjects using the proposed method.
format	Article
author	Shams, Wafaa Khazaal Abdul Rahman, Abdul Wahab Alshaikhli, Imad Fakhri Taha
author_facet	Shams, Wafaa Khazaal Abdul Rahman, Abdul Wahab Alshaikhli, Imad Fakhri Taha
author_sort	Shams, Wafaa Khazaal
title	Affective computing model using source-temporal domain
title_short	Affective computing model using source-temporal domain
title_full	Affective computing model using source-temporal domain
title_fullStr	Affective computing model using source-temporal domain
title_full_unstemmed	Affective computing model using source-temporal domain
title_sort	affective computing model using source-temporal domain
publisher	Elsevier
publishDate	2013
url	http://irep.iium.edu.my/34639/ http://irep.iium.edu.my/34639/ http://irep.iium.edu.my/34639/ http://irep.iium.edu.my/34639/1/Affective_computing_model_using_source-temporal_domain.pdf
first_indexed	2023-09-18T20:49:52Z
last_indexed	2023-09-18T20:49:52Z
_version_	1777409921749352448

Affective computing model using source-temporal domain

Similar Items