Group Differences in Facial Emotion Expression in Autism: Evidence for the Utility of Machine Classification

Behav Ther. 2019 Jul;50(4):828-838. doi: 10.1016/j.beth.2018.12.004. Epub 2018 Dec 21.

Abstract

Effective social communication relies, in part, on accurate nonverbal expression of emotion. To evaluate the nature of facial emotion expression (FEE) deficits in children with autism spectrum disorder (ASD), we compared 20 youths with ASD to a sample of typically developing (TD) youth (n = 20) using a machine-based classifier of FEE. Results indicate group differences in FEE for overall accuracy across emotions. In particular, a significant group difference in accuracy of FEE was observed when participants were prompted by a video of a human expressing an emotion, F(2, 36) = 4.99, p = .032, η2 = .12. Specifically, youth with ASD made significantly more errors in FEE relative to TD youth. Findings support continued refinement of machine-based approaches to assess and potentially remediate FEE impairment in youth with ASD.

Keywords: autism spectrum disorder; facial emotion expression; machine learning.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Autism Spectrum Disorder / psychology*
  • Child
  • Emotions*
  • Facial Expression*
  • Female
  • Humans
  • Male