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Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics

Thermal infrared imaging has been proposed as a potential system for the computational assessment of human autonomic nervous activity and psychophysiological states in a contactless and noninvasive way. Through bioheat modeling of facial thermal imagery, several vital signs can be extracted, includi...

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Detalles Bibliográficos
Autores principales: Cardone, Daniela, Pinti, Paola, Merla, Arcangelo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4538766/
https://www.ncbi.nlm.nih.gov/pubmed/26339284
http://dx.doi.org/10.1155/2015/984353
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author Cardone, Daniela
Pinti, Paola
Merla, Arcangelo
author_facet Cardone, Daniela
Pinti, Paola
Merla, Arcangelo
author_sort Cardone, Daniela
collection PubMed
description Thermal infrared imaging has been proposed as a potential system for the computational assessment of human autonomic nervous activity and psychophysiological states in a contactless and noninvasive way. Through bioheat modeling of facial thermal imagery, several vital signs can be extracted, including localized blood perfusion, cardiac pulse, breath rate, and sudomotor response, since all these parameters impact the cutaneous temperature. The obtained physiological information could then be used to draw inferences about a variety of psychophysiological or affective states, as proved by the increasing number of psychophysiological studies using thermal infrared imaging. This paper presents therefore a review of the principal achievements of thermal infrared imaging in computational physiology with regard to its capability of monitoring psychophysiological activity.
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spelling pubmed-45387662015-09-03 Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics Cardone, Daniela Pinti, Paola Merla, Arcangelo Comput Math Methods Med Review Article Thermal infrared imaging has been proposed as a potential system for the computational assessment of human autonomic nervous activity and psychophysiological states in a contactless and noninvasive way. Through bioheat modeling of facial thermal imagery, several vital signs can be extracted, including localized blood perfusion, cardiac pulse, breath rate, and sudomotor response, since all these parameters impact the cutaneous temperature. The obtained physiological information could then be used to draw inferences about a variety of psychophysiological or affective states, as proved by the increasing number of psychophysiological studies using thermal infrared imaging. This paper presents therefore a review of the principal achievements of thermal infrared imaging in computational physiology with regard to its capability of monitoring psychophysiological activity. Hindawi Publishing Corporation 2015 2015-08-03 /pmc/articles/PMC4538766/ /pubmed/26339284 http://dx.doi.org/10.1155/2015/984353 Text en Copyright © 2015 Daniela Cardone et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Cardone, Daniela
Pinti, Paola
Merla, Arcangelo
Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics
title Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics
title_full Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics
title_fullStr Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics
title_full_unstemmed Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics
title_short Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics
title_sort thermal infrared imaging-based computational psychophysiology for psychometrics
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4538766/
https://www.ncbi.nlm.nih.gov/pubmed/26339284
http://dx.doi.org/10.1155/2015/984353
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