Cargando…

Emotion analysis in children through facial emissivity of infrared thermal imaging

Physiological signals may be used as objective markers to identify emotions, which play relevant roles in social and daily life. To measure these signals, the use of contact-free techniques, such as Infrared Thermal Imaging (IRTI), is indispensable to individuals who have sensory sensitivity. The go...

Descripción completa

Detalles Bibliográficos
Autores principales: Goulart, Christiane, Valadão, Carlos, Delisle-Rodriguez, Denis, Caldeira, Eliete, Bastos, Teodiano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426206/
https://www.ncbi.nlm.nih.gov/pubmed/30893343
http://dx.doi.org/10.1371/journal.pone.0212928
_version_ 1783404968024211456
author Goulart, Christiane
Valadão, Carlos
Delisle-Rodriguez, Denis
Caldeira, Eliete
Bastos, Teodiano
author_facet Goulart, Christiane
Valadão, Carlos
Delisle-Rodriguez, Denis
Caldeira, Eliete
Bastos, Teodiano
author_sort Goulart, Christiane
collection PubMed
description Physiological signals may be used as objective markers to identify emotions, which play relevant roles in social and daily life. To measure these signals, the use of contact-free techniques, such as Infrared Thermal Imaging (IRTI), is indispensable to individuals who have sensory sensitivity. The goal of this study is to propose an experimental design to analyze five emotions (disgust, fear, happiness, sadness and surprise) from facial thermal images of typically developing (TD) children aged 7–11 years using emissivity variation, as recorded by IRTI. For the emotion analysis, a dataset considered emotional dimensions (valence and arousal), facial bilateral sides and emotion classification accuracy. The results evidence the efficiency of the experimental design with interesting findings, such as the correlation between the valence and the thermal decrement in nose; disgust and happiness as potent triggers of facial emissivity variations; and significant emissivity variations in nose, cheeks and periorbital regions associated with different emotions. Moreover, facial thermal asymmetry was revealed with a distinct thermal tendency in the cheeks, and classification accuracy reached a mean value greater than 85%. From the results, the emissivity variations were an efficient marker to analyze emotions in facial thermal images, and IRTI was confirmed to be an outstanding technique to study emotions. This study contributes a robust dataset to analyze the emotions of 7-11-year-old TD children, an age range for which there is a gap in the literature.
format Online
Article
Text
id pubmed-6426206
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-64262062019-04-02 Emotion analysis in children through facial emissivity of infrared thermal imaging Goulart, Christiane Valadão, Carlos Delisle-Rodriguez, Denis Caldeira, Eliete Bastos, Teodiano PLoS One Research Article Physiological signals may be used as objective markers to identify emotions, which play relevant roles in social and daily life. To measure these signals, the use of contact-free techniques, such as Infrared Thermal Imaging (IRTI), is indispensable to individuals who have sensory sensitivity. The goal of this study is to propose an experimental design to analyze five emotions (disgust, fear, happiness, sadness and surprise) from facial thermal images of typically developing (TD) children aged 7–11 years using emissivity variation, as recorded by IRTI. For the emotion analysis, a dataset considered emotional dimensions (valence and arousal), facial bilateral sides and emotion classification accuracy. The results evidence the efficiency of the experimental design with interesting findings, such as the correlation between the valence and the thermal decrement in nose; disgust and happiness as potent triggers of facial emissivity variations; and significant emissivity variations in nose, cheeks and periorbital regions associated with different emotions. Moreover, facial thermal asymmetry was revealed with a distinct thermal tendency in the cheeks, and classification accuracy reached a mean value greater than 85%. From the results, the emissivity variations were an efficient marker to analyze emotions in facial thermal images, and IRTI was confirmed to be an outstanding technique to study emotions. This study contributes a robust dataset to analyze the emotions of 7-11-year-old TD children, an age range for which there is a gap in the literature. Public Library of Science 2019-03-20 /pmc/articles/PMC6426206/ /pubmed/30893343 http://dx.doi.org/10.1371/journal.pone.0212928 Text en © 2019 Goulart et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Goulart, Christiane
Valadão, Carlos
Delisle-Rodriguez, Denis
Caldeira, Eliete
Bastos, Teodiano
Emotion analysis in children through facial emissivity of infrared thermal imaging
title Emotion analysis in children through facial emissivity of infrared thermal imaging
title_full Emotion analysis in children through facial emissivity of infrared thermal imaging
title_fullStr Emotion analysis in children through facial emissivity of infrared thermal imaging
title_full_unstemmed Emotion analysis in children through facial emissivity of infrared thermal imaging
title_short Emotion analysis in children through facial emissivity of infrared thermal imaging
title_sort emotion analysis in children through facial emissivity of infrared thermal imaging
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6426206/
https://www.ncbi.nlm.nih.gov/pubmed/30893343
http://dx.doi.org/10.1371/journal.pone.0212928
work_keys_str_mv AT goulartchristiane emotionanalysisinchildrenthroughfacialemissivityofinfraredthermalimaging
AT valadaocarlos emotionanalysisinchildrenthroughfacialemissivityofinfraredthermalimaging
AT delislerodriguezdenis emotionanalysisinchildrenthroughfacialemissivityofinfraredthermalimaging
AT caldeiraeliete emotionanalysisinchildrenthroughfacialemissivityofinfraredthermalimaging
AT bastosteodiano emotionanalysisinchildrenthroughfacialemissivityofinfraredthermalimaging