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Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects

Facial infra-red imaging (IRI) is a contact-free technique complimenting the traditional psychophysiological measures to characterize physiological profile. However, its full potential in affective research is arguably unmet due to the analytical challenges it poses. Here we acquired facial IRI data...

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Autores principales: Sonkusare, Saurabh, Breakspear, Michael, Pang, Tianji, Nguyen, Vinh Thai, Frydman, Sascha, Guo, Christine Cong, Aburn, Matthew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187483/
https://www.ncbi.nlm.nih.gov/pubmed/34103607
http://dx.doi.org/10.1038/s41598-021-91578-5
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author Sonkusare, Saurabh
Breakspear, Michael
Pang, Tianji
Nguyen, Vinh Thai
Frydman, Sascha
Guo, Christine Cong
Aburn, Matthew J.
author_facet Sonkusare, Saurabh
Breakspear, Michael
Pang, Tianji
Nguyen, Vinh Thai
Frydman, Sascha
Guo, Christine Cong
Aburn, Matthew J.
author_sort Sonkusare, Saurabh
collection PubMed
description Facial infra-red imaging (IRI) is a contact-free technique complimenting the traditional psychophysiological measures to characterize physiological profile. However, its full potential in affective research is arguably unmet due to the analytical challenges it poses. Here we acquired facial IRI data, facial expressions and traditional physiological recordings (heart rate and skin conductance) from healthy human subjects whilst they viewed a 20-min-long unedited emotional movie. We present a novel application of motion correction and the results of spatial independent component analysis of the thermal data. Three distinct spatial components are recovered associated with the nose, the cheeks and respiration. We first benchmark this methodology against a traditional nose-tip region-of-interest based technique showing an expected similarity of signals extracted by these methods. We then show significant correlation of all the physiological responses across subjects, including the thermal signals, suggesting common dynamic shifts in emotional state induced by the movie. In sum, this study introduces an innovative approach to analyse facial IRI data and highlights the potential of thermal imaging to robustly capture emotion-related changes induced by ecological stimuli.
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spelling pubmed-81874832021-06-09 Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects Sonkusare, Saurabh Breakspear, Michael Pang, Tianji Nguyen, Vinh Thai Frydman, Sascha Guo, Christine Cong Aburn, Matthew J. Sci Rep Article Facial infra-red imaging (IRI) is a contact-free technique complimenting the traditional psychophysiological measures to characterize physiological profile. However, its full potential in affective research is arguably unmet due to the analytical challenges it poses. Here we acquired facial IRI data, facial expressions and traditional physiological recordings (heart rate and skin conductance) from healthy human subjects whilst they viewed a 20-min-long unedited emotional movie. We present a novel application of motion correction and the results of spatial independent component analysis of the thermal data. Three distinct spatial components are recovered associated with the nose, the cheeks and respiration. We first benchmark this methodology against a traditional nose-tip region-of-interest based technique showing an expected similarity of signals extracted by these methods. We then show significant correlation of all the physiological responses across subjects, including the thermal signals, suggesting common dynamic shifts in emotional state induced by the movie. In sum, this study introduces an innovative approach to analyse facial IRI data and highlights the potential of thermal imaging to robustly capture emotion-related changes induced by ecological stimuli. Nature Publishing Group UK 2021-06-08 /pmc/articles/PMC8187483/ /pubmed/34103607 http://dx.doi.org/10.1038/s41598-021-91578-5 Text en © Crown 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Sonkusare, Saurabh
Breakspear, Michael
Pang, Tianji
Nguyen, Vinh Thai
Frydman, Sascha
Guo, Christine Cong
Aburn, Matthew J.
Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects
title Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects
title_full Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects
title_fullStr Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects
title_full_unstemmed Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects
title_short Data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects
title_sort data-driven analysis of facial thermal responses and multimodal physiological consistency among subjects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187483/
https://www.ncbi.nlm.nih.gov/pubmed/34103607
http://dx.doi.org/10.1038/s41598-021-91578-5
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