EEG-based valence level recognition for real-time applications

Emotions are important in human-computer interaction. Emotions could be classified based on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of emotions even without discrete emotion labels. In this paper, we proposed a real-time EEG-based subject-dependent valence leve...

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Main Authors: Liu, Yisi., Sourina, Olga.
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/84767
http://hdl.handle.net/10220/12706
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-847672020-03-07T13:24:45Z EEG-based valence level recognition for real-time applications Liu, Yisi. Sourina, Olga. School of Electrical and Electronic Engineering International Conference on Cyberworlds (2012 : Darmstadt, Germany) DRNTU::Engineering::Electrical and electronic engineering Emotions are important in human-computer interaction. Emotions could be classified based on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of emotions even without discrete emotion labels. In this paper, we proposed a real-time EEG-based subject-dependent valence level recognition algorithm, where the thresholds were used to identify different levels of the valence dimension of the human emotion. The algorithm was tested by using the EEG data labeled with valence levels. The algorithm could identify valence levels continuously. The algorithm was tested with the experiment data and with the benchmark affective EEG database DEAP where up to 9 levels of valence dimension with high/low dominance were recognized. Then, the algorithm was applied to recognize 16 emotions defined by high/low arousal, high/low dominance and 4 levels of valence. At least 14 electrodes should be used to get the better accuracy. The proposed algorithm could be implemented in different real-time applications such as emotional avatar and E-learning systems. 2013-08-01T02:13:37Z 2019-12-06T15:50:55Z 2013-08-01T02:13:37Z 2019-12-06T15:50:55Z 2012 2012 Conference Paper Liu, Y.,& Sourina, O. (2012). EEG-based Valence Level Recognition for Real-Time Applications. 2012 International Conference on Cyberworlds, 53-60. https://hdl.handle.net/10356/84767 http://hdl.handle.net/10220/12706 10.1109/CW.2012.15 en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Liu, Yisi.
Sourina, Olga.
EEG-based valence level recognition for real-time applications
description Emotions are important in human-computer interaction. Emotions could be classified based on 3-dimensional Valence-Arousal-Dominance model which allows defining any number of emotions even without discrete emotion labels. In this paper, we proposed a real-time EEG-based subject-dependent valence level recognition algorithm, where the thresholds were used to identify different levels of the valence dimension of the human emotion. The algorithm was tested by using the EEG data labeled with valence levels. The algorithm could identify valence levels continuously. The algorithm was tested with the experiment data and with the benchmark affective EEG database DEAP where up to 9 levels of valence dimension with high/low dominance were recognized. Then, the algorithm was applied to recognize 16 emotions defined by high/low arousal, high/low dominance and 4 levels of valence. At least 14 electrodes should be used to get the better accuracy. The proposed algorithm could be implemented in different real-time applications such as emotional avatar and E-learning systems.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Liu, Yisi.
Sourina, Olga.
format Conference or Workshop Item
author Liu, Yisi.
Sourina, Olga.
author_sort Liu, Yisi.
title EEG-based valence level recognition for real-time applications
title_short EEG-based valence level recognition for real-time applications
title_full EEG-based valence level recognition for real-time applications
title_fullStr EEG-based valence level recognition for real-time applications
title_full_unstemmed EEG-based valence level recognition for real-time applications
title_sort eeg-based valence level recognition for real-time applications
publishDate 2013
url https://hdl.handle.net/10356/84767
http://hdl.handle.net/10220/12706
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