A family of neurodevelopmental biomarkers extracted from a statistical analysis of kinematic data measured with high-definition sensors

There is significant interest in finding quantitative ways of diagnosing psychiatric disorders. Most clinical studies use qualitative assessments, based on clinical interview and behavioral observations. In our research program, we have concentrated on studying subjects with neurodevelopmental disorders under the hypothesis that significant diagnostic information is contained within how people move. We used as an experimental paradigm, targeted reaching movements and examining kinematic variables at millisecond time scales. In our previous studies [1,2] of subjects with Autism Spectrum Disorder (ASD) , we analyzed the randomness of maximal velocity. We reported that the probability distribution for its maximum can be mapped directly to ASD diagnosis. We now extend these studies of velocity randomness to participants with Attention Deficit Hyperactive Disorder (ADHD), and comorbid ASD+ADHD [3]. We identified a new family of biomarkers related to the ratio of an overlap of distribution areas under their curves.