From Research to Practice

Abstract

Smart technologies (wearable and mobile devices) show tremendous potential in the detection, diagnosis, and management of Autism Spectrum Disorder (ASD) by enabling continuous real-time data collection, identifying effective treatment strategies, and supporting intervention design and delivery. Though promising, effective utilization of smart technology in aiding ASD is still limited. We propose a set of implications to guide the design of ASD-support technology by analyzing 149 peer-reviewed articles focused on children with autism from ACM Digital Library, IEEE Xplore, and PubMed. Our analysis reveals that technology should facilitate real-time detection and identification of points-of-interest, adapt its behavior driven by the real-time affective state of the user, utilize familiar and unfamiliar features depending on user-context, and aid in revealing even minuscule progress made by children with autism. Our findings indicate that such technology should strive to blend-in with everyday objects. Moreover, gradual exposure and desensitization may facilitate successful adaptation of novel technology.