1. Toward identifying behavioral risk markers for mental health disorders: an assistive system for monitoring children’s movements in a preschool classroom.
- Author
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Walczak, Nicholas, Fasching, Joshua, Cullen, Kathryn, Morellas, Vassilios, and Papanikolopoulos, Nikolaos
- Subjects
SENSORIMOTOR integration ,MEDICAL care of people with mental illness ,PATHOLOGICAL psychology ,DETECTORS ,ARTIFICIAL intelligence - Abstract
Mental health disorders are a leading cause of disability in North America. An important aspect in treating mental disorders is early intervention, which dramatically increases the probability of positive outcomes; however, early intervention hinges upon knowledge and detection of risk markers for particular disorders. Ideally, the screening of these risk markers should occur in a community setting, but this is time-consuming and resource-intensive. Assistive systems could greatly aid in the detection of risk markers in a hectic environment like a preschool classroom. This paper presents a multi-sensor system consisting of 5 RGB-D sensors that detects and tracks the location of occupants in a preschool classroom and computes a measure of activity level and proximity between individuals, an index of social functioning. This assistive system operates in near real-time and is able to track occupants and deal with difficult situations both with occupants (children sitting and laying on the ground, hugging, playing dress-up, etc) and their environment (i.e., changing light levels from artificial and natural sources). The system is installed at, and validated on recordings taken from, the Shirley G. Moore Lab School, a research preschool classroom at the University of Minnesota. The work described herein provides the initial groundwork for monitoring basic elements of child behavior; future efforts will be geared toward identifying and tracking more sophisticated behavioral signatures relevant to mental health. [ABSTRACT FROM AUTHOR]
- Published
- 2018
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