Facial Expression Databases and Autism Spectrum Disorder: A Scoping Review

Abstract

Emotion recognition (ER) deficit in autism spectrum disorder (ASD) is widely accepted, and a variety of research was done to assess the deficit in ER under various conditions and intervention research to augment emotion recognition in mostly children with ASD. This scoping review attempted to summarize the diverse research in the context of ER in ASD with a focus on the facial expression databases used for research and intervention. PRISMA-ScR guidelines were followed, and 80 studies were selected after a search from electronic research databases like Web of Science and PubMed with predefined inclusion and exclusion criteria. The trends indicate a small sample size with mostly children as a sample and the ASD group with their matched counterparts. The results show mixed findings; the majority of work indicates a deficit in facial emotion recognition in ASD, but under certain stimuli and conditions, ASD performs well in facial emotion recognition. The interventions showed promising results with increased ER ability in children with ASD. The review also focused on the moderating factors in the study of ER, such as age, IQ, comorbidity, task paradigm, and cultural factors. A small subset of facial expression databases was widely used in the research and intervention, and it has been developed and validated in Western countries. Research gaps were highlighted, and recommendations for future directions were mentioned.