Guess What? Towards Understanding Autism from Structured Video Using Facial Affect

• Published in: Journal of healthcare informatics research Vol. 3; no. 1; pp. 43 - 66
• Main Authors: Kalantarian, Haik, Washington, Peter, Schwartz, Jessey, Daniels, Jena, Haber, Nick, Wall, Dennis P.
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 15.03.2019
• Subjects: Biomedical Engineering and Bioengineering; Computational Biology/Bioinformatics; Computational Intelligence; Computer Science; Data Mining and Knowledge Discovery; Health Informatics; Research Article; Autism; Mobile; Emotion
• ISSN: 2509-4971; 2509-498X
• DOI: 10.1007/s41666-018-0034-9

Autism Spectrum Disorder (ASD) is a condition affecting an estimated 1 in 59 children in the United States. Due to delays in diagnosis and imbalances in coverage, it is necessary to develop new methods of care delivery that can appropriately empower children and caregivers by capitalizing on mobile tools and wearable devices for use outside of clinical settings. In this paper, we present a mobile charades-style game, Guess What? , used for the acquisition of structured video from children with ASD for behavioral disease research. We then apply face tracking and emotion recognition algorithms to videos acquired through Guess What? game play. By analyzing facial affect in response to various prompts, we demonstrate that engagement and facial affect can be quantified and measured using real-time image processing algorithms: an important first-step for future therapies, at-home screenings, and outcome measures based on home video. Our study of eight subjects demonstrates the efficacy of this system for deriving highly emotive structured video from children with ASD through an engaging gamified mobile platform, while revealing the most efficacious prompts and categories for producing diverse emotion in participants.