Detecting risk-markers in children in a preschool classroom
Early intervention in mental disorders can dramatically increase an individual's quality of life. Additionally, when symptoms of mental illness appear in childhood or adolescence, they represent the later stages of a process that began years earlier. One goal of psychiatric research is to identify risk-markers: genetic, neural, behavioral and/or social deviations that indicate elevated risk of a particular mental disorder. Ideally, screening of risk-markers should occur in a community setting, and not a clinical setting which may be time-consuming and resource-intensive. Given this situation, a system for automatically detecting risk-markers in children would be highly valuable. In this paper, we describe such a system that has been installed at the Shirley G. Moore Lab School, a research pre-school at the University of Minnesota. This system consists of multiple RGB+D sensors and is able to detect children and adults in the classroom, tracking them as they move around the room. We use the tracking results to extract high-level information about the behavior and social interaction of children, that can then be used to screen for early signs of mental disorders.