NDLI: Emotion recognition system using brain and peripheral signals: Using correlation dimension to improve the results of EEG

Content Provider	IEEE Xplore Digital Library
Author	Khalili, Z. Moradi, M.H.
Copyright Year	2009
Description	Author affiliation: Biomedical Engineering Faculty, Amirkabir University of Technology, Tehran, Iran (Khalili, Z.; Moradi, M.H.)
Abstract	This paper proposed a multimodal fusion between brain and peripheral signals for emotion detection. The input signals were electroencephalogram, galvanic skin resistance, temperature, blood pressure and respiration, which can reflect the influence of emotion on the central nervous system and autonomic nervous system respectively. The acquisition protocol is based on a subset of pictures which correspond to three specific areas of valance-arousal emotional space (positively excited, negatively excited, and calm). The features extracted from input signals, and to improve the results, correlation dimension as a strong nonlinear feature is used for brain signals. The performance of the Quadratic Discriminant Classifier has been evaluated on different feature sets: peripheral signals, EEG's, and both. In comparison among the results of different feature sets, EEG signals seem to perform better than other physiological signals, and the results confirm the interest of using brain signals as peripherals in emotion assessment. According to the improvement in EEG results compare in each raw of the table, it seems that nonlinear features would lead to better understanding of how emotional activities work.
Starting Page	1571
Ending Page	1575
File Size	1148700
Page Count	5
File Format	PDF
ISBN	9781424435487
ISSN	10987576
DOI	10.1109/IJCNN.2009.5178854
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Emotion recognition Electroencephalography Signal detection Galvanizing Skin Temperature Blood pressure Central nervous system Autonomic nervous system Protocols correlation dimension Emotion EEG peripheralsignals feature extraction classification
Content Type	Text
Resource Type	Article

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