2020/02/16 by Catalin Voss, Peter Washington, Voss, Catalin +20
Computer Science · Neuroscience · Psychology · Social Sciences · #Autism Spectrum Disorder Research #Child Development and Digital Technology #Digital Mental Health Interventions #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #cs.HC
paper · pdf · doi:10.48550/arxiv.2002.06581
UbiComp ISWC 2016
arxiv created 2020/02/16 · openalex publication_date 2020/02/16 · arxiv updated 2020/02/18 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
We have developed a system for automatic facial expression recognition, which runs on Google Glass and delivers real-time social cues to the wearer. We evaluate the system as a behavioral aid for children with Autism Spectrum Disorder (ASD), who can greatly benefit from real-time non-invasive emotional cues and are more sensitive to sensory input than neurotypically developing children. In addition, we present a mobile application that enables users of the wearable aid to review their videos along with auto-curated emotional information on the video playback bar. This integrates our learning aid into the context of behavioral therapy. Expanding on our previous work describing in-lab trials, this paper presents our system and application-level design decisions in depth as well as the interface learnings gathered during the use of the system by multiple children with ASD in an at-home iterative trial.