Applied Sciences (Aug 2022)

Test–Retest Reliability in Automated Emotional Facial Expression Analysis: Exploring FaceReader 8.0 on Data from Typically Developing Children and Children with Autism

  • Zsófia Borsos,
  • Zoltán Jakab,
  • Krisztina Stefanik,
  • Bianka Bogdán,
  • Miklos Gyori

DOI
https://doi.org/10.3390/app12157759
Journal volume & issue
Vol. 12, no. 15
p. 7759

Abstract

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Automated emotional facial expression analysis (AEFEA) is used widely in applied research, including the development of screening/diagnostic systems for atypical human neurodevelopmental conditions. The validity of AEFEA systems has been systematically studied, but their test–retest reliability has not been researched thus far. We explored the test–retest reliability of a specific AEFEA software, Noldus FaceReader 8.0 (FR8; by Noldus Information Technology). We collected intensity estimates for 8 repeated emotions through FR8 from facial video recordings of 60 children: 31 typically developing children and 29 children with autism spectrum disorder. Test–retest reliability was imperfect in 20% of cases, affecting a substantial proportion of data points; however, the test–retest differences were small. This shows that the test–retest reliability of FR8 is high but not perfect. A proportion of cases which initially failed to show perfect test–retest reliability reached it in a subsequent analysis by FR8. This suggests that repeated analyses by FR8 can, in some cases, lead to the “stabilization” of emotion intensity datasets. Under ANOVA, the test–retest differences did not influence the pattern of cross-emotion and cross-group effects and interactions. Our study does not question the validity of previous results gained by AEFEA technology, but it shows that further exploration of the test–retest reliability of AEFEA systems is desirable.

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