Group Differences in Facial Emotion Expression in Autism: Evidence for the Utility of Machine Classification. Issue 4 (July 2019)

• Record Type: Journal Article
• Authors: Capriola-Hall, Nicole N.; Wieckowski, Andrea Trubanova; Swain, Deanna; Tech, Virginia; Aly, Sherin; Youssef, Amira; Abbott, A. Lynn; White, Susan W.
• Is Part Of: Behavior therapy. Volume 50:Issue 4(2019)
• Page Start: 828
• Page End: 838
• Publication Date: 2019-07
• Subjects: autism spectrum disorder -- facial emotion expression -- machine learning; Behavior therapy -- Periodicals; 616.8914205
• DOI: 10.1016/j.beth.2018.12.004
• Languages: English
• ISSNs: 0005-7894

Abstract

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, η 2 = .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. Highlights: An emotion recognition system (FEET) detected differences in emotion expression There was a positive association between human coded emotions and the FEET system Youth with Autism (ASD) were compared to controls in facial emotion expression Youth with ASD showed lower accuracy in emotion expression for human faces