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Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring

This study validates automated emotion and action unit (AU) coding applying FaceReader 7 to a dataset of standardized facial expressions of six basic emotions (Standardized and Motivated Facial Expressions of Emotion). Percentages of correctly and falsely classified expressions are reported. The val...

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Detalles Bibliográficos
Autores principales: Skiendziel, Tanja, Rösch, Andreas G., Schultheiss, Oliver C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797095/
https://www.ncbi.nlm.nih.gov/pubmed/31622426
http://dx.doi.org/10.1371/journal.pone.0223905
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author Skiendziel, Tanja
Rösch, Andreas G.
Schultheiss, Oliver C.
author_facet Skiendziel, Tanja
Rösch, Andreas G.
Schultheiss, Oliver C.
author_sort Skiendziel, Tanja
collection PubMed
description This study validates automated emotion and action unit (AU) coding applying FaceReader 7 to a dataset of standardized facial expressions of six basic emotions (Standardized and Motivated Facial Expressions of Emotion). Percentages of correctly and falsely classified expressions are reported. The validity of coding AUs is provided by correlations between the automated analysis and manual Facial Action Coding System (FACS) scoring for 20 AUs. On average 80% of the emotional facial expressions are correctly classified. The overall validity of coding AUs is moderate with the highest validity indicators for AUs 1, 5, 9, 17 and 27. These results are compared to the performance of FaceReader 6 in previous research, with our results yielding comparable validity coefficients. Practical implications and limitations of the automated method are discussed.
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spelling pubmed-67970952019-10-20 Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring Skiendziel, Tanja Rösch, Andreas G. Schultheiss, Oliver C. PLoS One Research Article This study validates automated emotion and action unit (AU) coding applying FaceReader 7 to a dataset of standardized facial expressions of six basic emotions (Standardized and Motivated Facial Expressions of Emotion). Percentages of correctly and falsely classified expressions are reported. The validity of coding AUs is provided by correlations between the automated analysis and manual Facial Action Coding System (FACS) scoring for 20 AUs. On average 80% of the emotional facial expressions are correctly classified. The overall validity of coding AUs is moderate with the highest validity indicators for AUs 1, 5, 9, 17 and 27. These results are compared to the performance of FaceReader 6 in previous research, with our results yielding comparable validity coefficients. Practical implications and limitations of the automated method are discussed. Public Library of Science 2019-10-17 /pmc/articles/PMC6797095/ /pubmed/31622426 http://dx.doi.org/10.1371/journal.pone.0223905 Text en © 2019 Skiendziel 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
Skiendziel, Tanja
Rösch, Andreas G.
Schultheiss, Oliver C.
Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring
title Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring
title_full Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring
title_fullStr Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring
title_full_unstemmed Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring
title_short Assessing the convergent validity between the automated emotion recognition software Noldus FaceReader 7 and Facial Action Coding System Scoring
title_sort assessing the convergent validity between the automated emotion recognition software noldus facereader 7 and facial action coding system scoring
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797095/
https://www.ncbi.nlm.nih.gov/pubmed/31622426
http://dx.doi.org/10.1371/journal.pone.0223905
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