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Autism often remains undiagnosed in adolescents and adults. Prior researchhas indicated that an autistic individual often shows atypical fixation andgaze patterns. In this short paper, we demonstrate that by monitoring a user'sgaze as they watch commonplace (i.e., not specialized, structured or coded)video, we can identify individuals with autism spectrum disorder. We recruited35 autistic and 25 non-autistic individuals, and captured their gaze using anoff-the-shelf eye tracker connected to a laptop. Within 15 seconds, ourapproach was 92.5% accurate at identifying individuals with an autismdiagnosis. We envision such automatic detection being applied during e.g., theconsumption of web media, which could allow for passive screening andadaptation of user interfaces.

Gaze-based Autism Detection for Adolescents and Young Adults using Prosaic Videos