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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Bibliographic Details
Published inPloS one Vol. 14; no. 10; p. e0223905
Main Authors Skiendziel, Tanja, Rösch, Andreas G, Schultheiss, Oliver C
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 17.10.2019
Public Library of Science (PLoS)
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Summary: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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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0223905