Detecting Thermal Emotional Profile

Yang Fu, Claude Frasson

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 Learning 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.

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Paper Citation


in Harvard Style

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, pages 142-151. DOI: 10.5220/0006007901420151


in Bibtex Style

@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},
}


in EndNote Style

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