Document Detail


Toward emotion aware computing: an integrated approach using multichannel neurophysiological recordings and affective visual stimuli.
MedLine Citation:
PMID:  20172835     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
This paper proposes a methodology for the robust classification of neurophysiological data into four emotional states collected during passive viewing of emotional evocative pictures selected from the International Affective Picture System. The proposed classification model is formed according to the current neuroscience trends, since it adopts the independency of two emotional dimensions, namely arousal and valence, as dictated by the bidirectional emotion theory, whereas it is gender-specific. A two-step classification procedure is proposed for the discrimination of emotional states between EEG signals evoked by pleasant and unpleasant stimuli, which also vary in their arousal/intensity levels. The first classification level involves the arousal discrimination. The valence discrimination is then performed. The Mahalanobis (MD) distance-based classifier and support vector machines (SVMs) were used for the discrimination of emotions. The achieved overall classification rates were 79.5% and 81.3% for the MD and SVM, respectively, significantly higher than in previous studies. The robust classification of objective emotional measures is the first step toward numerous applications within the sphere of human-computer interaction.
Authors:
Christos A Frantzidis; Charalampos Bratsas; Christos L Papadelis; Evdokimos Konstantinidis; Costas Pappas; Panagiotis D Bamidis
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2010-02-17
Journal Detail:
Title:  IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society     Volume:  14     ISSN:  1558-0032     ISO Abbreviation:  IEEE Trans Inf Technol Biomed     Publication Date:  2010 May 
Date Detail:
Created Date:  2010-07-27     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9712259     Medline TA:  IEEE Trans Inf Technol Biomed     Country:  United States    
Other Details:
Languages:  eng     Pagination:  589-97     Citation Subset:  IM    
Affiliation:
Laboratory of Medical Informatics, Medical School, Aristotle University of Thessaloniki, Thessaloniki 54124, Greece. christos.frantzidis@gmail.com
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