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Authors: Yang Fu and Claude Frasson

Affiliation: University of Montreal, Canada

ISBN: 978-989-758-197-7

ISSN: 2184-321X

Keyword(s): Emotion Recognition, IAPS, Skin Temperature, Thermal Emotional Profile, Machine Learning, EEG, HMM (Hidden Markov Model), Infrared Camera.

Related Ontology Subjects/Areas/Topics: Affective Computing ; Biomedical Devices for Computer Interaction ; Biomedical Engineering ; Computer Graphics and Visualization of Physiological Data ; Devices ; Health Information Systems ; Human-Computer Interaction ; Methodologies and Methods ; Physiological Computing Systems ; Video and Image Analysis for Physiological Computing

Abstract: Human can react emotionally to specific situations provoking some physiological changes that can be detected using a variety of devices, facial expression, electrodermal activity, and EEG systems are among the efficient devices which can assess the emotional reactions. However, emotions can trigger some small changes in blood flow with an impact on skin temperature. In the present research we use EEG and a thermal camera to determine the emotional profile of a user submitted to a set of emotional pictures. Six experiments were performed to study the thermal reactions to emotions, and in each experiment, 80 selected standard stimuli pictures of 20 various emotional profiles from IAPS (a database of emotional images) were displayed to participants every three seconds. An infrared camera and EEG were used to capture both thermal pictures of participants and their electrical brain activities. We used several area of the face to train a classifier for emotion recognition using Machine Lear ning models. Results indicate that some specific areas are more significant than others to show a change in temperature. These changes are also slower than with the EEG signal. Two methods were used to train the HMM, one is training classifier per the participant self data (participant-independent), another is training classifier based on all participants` thermal data (participant-dependent). The result showed the later method brings more accuracy emotion recognition. (More)

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Paper citation in several formats:
Fu, Y. and Frasson, C. (2016). Detecting Thermal Emotional Profile.In Proceedings of the 3rd International Conference on Physiological Computing Systems - Volume 1: PhyCS, ISBN 978-989-758-197-7, ISSN 2184-321X, pages 142-151. DOI: 10.5220/0006007901420151

@conference{phycs16,
author={Yang Fu. and Claude Frasson.},
title={Detecting Thermal Emotional Profile},
booktitle={Proceedings of the 3rd International Conference on Physiological Computing Systems - Volume 1: PhyCS,},
year={2016},
pages={142-151},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006007901420151},
isbn={978-989-758-197-7},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Physiological Computing Systems - Volume 1: PhyCS,
TI - Detecting Thermal Emotional Profile
SN - 978-989-758-197-7
AU - Fu, Y.
AU - Frasson, C.
PY - 2016
SP - 142
EP - 151
DO - 10.5220/0006007901420151

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