Impairment in facial emotion recognition (FER) and facial emotion expression (FEE), often documented in autism spectrum disorder (ASD), are believed to contribute to the observed core social-communication disability that characterizes this disorder. Moreover, impaired FER and FEE are frequently seen in other disorders and problem behaviors. We describe the development of a novel system to detect and give real-time feedback on these processes, termed facial emotion expression training (FEET), an automated, gamelike system that is based on 3-dimensional sensing (Kinect) technology. A sample of 40 children (n = 20 ASD, n = 20 typically developing) interacted with our prototype system, which presented audiovisual stimuli and assessed responses of participants. Overall, consumer satisfaction ratings were high, and youth with ASD reported enjoying interacting with the system more than did the typical youth. Results suggest that new technology-based interventions are acceptable to consumers and viable for use in remediation of transdiagnostic processes, such as FER and FEE. Implications for future technology-based intervention to target transdiagnostic processes are discussed.
Keywords: affective computing; autism; facial emotion expression; facial emotion recognition; technology.
Copyright © 2018. Published by Elsevier Ltd.