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ThinkMind // ACHI 2016, The Ninth International Conference on Advances in Computer-Human Interactions // View article achi_2016_12_40_20304


Autonomic Nervous Activity estimation algorithm with Facial Skin Thermal Image

Authors:
Tota Mizuno
Shusuke Kawazura
Kota Akehi
Shogo Matsuno
Hirotoshi Asano
Kazuyuki Mito
Naoaki Itakura

Keywords: Facial thermal image; Nasal skin temperature; Mental work-Load

Abstract:
The aim of this study was to achieve the absolute evaluation of mental workload (MWL) by proposing a novel algorithm for the evaluation and estimation of autonomic nervous activity with facial thermal imaging. Innovation in Information and Communication Technology(ICT) has resulted in workers experiencing an increasing mental workload, which is caused by using the computer. In our research group we have studied a method to evaluate and estimate autonomic nervous activity using facial thermal imaging as measured by infrared thermography. Previous methods extracted the forehead and nose as a method for performing the evaluation and estimation using the temperature difference. However, this approach does not consider the area. The proposed method enables parts or areas of temperature change other than the nose to be captured. This presents the possibility of accurate evaluation and estimation at levels that are more sensitive than the conventional method. In addition, there is the possibility of absolute evaluation by using one thermal image of the face. We also examined whether further high-precision evaluation and estimation would be possible. Our results showed the proposed method to be a highly accurate nasal skin temperature (NST) evaluation method compared to results obtained in previous studies.

Pages: 262 to 266

Copyright: Copyright (c) IARIA, 2016

Publication date: April 24, 2016

Published in: conference

ISSN: 2308-4138

ISBN: 978-1-61208-468-8

Location: Venice, Italy

Dates: from April 24, 2016 to April 28, 2016

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