Early diagnostic assessments of neurodivergent disorders (NDD), remains a major clinical challenge. We address this problem by pursuing the hypothesis that there is important cognitive information about NDD conditions contained in the way individuals move, when viewed at millisecond time scales. We approach the NDD assessment problem in two complementary ways. First, we applied supervised deep learning (DL) techniques to identify participants with autism spectrum disorder (ASD),…
