The Use of Immersive Environments for the Early Detection and Treatment of Neuropsychiatric Disorders
Year: 2021
Type: article
Abstract: Neuropsychiatric disorders are highly prevalent conditions with significant individual, societal, and economic impacts. A major challenge in the diagnosis and treatment of these conditions is the lack of sensitive, reliable, objective, quantitative tools to inform diagnosis, and measure symptom severity. Currently available assays rely on self-reports and clinician observations, leading to subjective analysis. As a step toward creating quantitative assays of neuropsychiatric symptoms, we propose an immersive environment to track behaviors relevant to neuropsychiatric symptomatology and to systematically study the effect of environmental contexts on certain behaviors. Moreover, the overarching theme leads to connected tele-psychiatry which can provide effective assessment.
Source: Frontiers in Digital Health
Authors: Robert F. K. Martin, Patrick Leppink-Shands, Matthew Tlachac, Megan DuBois, Christine Conelea, Suma Jacob, Vassilios Morellas, Theodore Morris, Nikolaos Papanikolopoulos
Institution: University of Minnesota
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,900
Funder: National Science Foundation
Awards: I/UCRC Phase I: Robots and Sensors for the Human Well-being, MRI: Development of an Instrument that Monitors Behaviors Associated with Obsessive-Compulsive Behaviors and Schizophrenia, MRI: Development of an Instrument that Performs Behavioral Analysis for Neuropsychiatric Disorders like Tourette Syndrome, Phase II IUCRC University of Minnesota: Center for Robots and Sensors for the Human Well-being
OpenAlex ID: W3128751033