The University of Texas at San Antonio (UTSA) announced an important development in their work with artificial intelligence (AI) which seeks to help improve learning applications for individuals diagnosed with autism spectrum disorder (ASD) and offering precision treatment plans. A wearable and AI laboratory will assist researchers in their efforts toward automating data collection and analysis of behavioral sensing data.
The project is a joint venture between UTSA’s Child and Adolescent Policy Research Institute (CAPRI) and the Secure AI Laboratory for Autonomy (AILA). When used in AR/VR, gameplay, and other digital platforms, these efforts would pave the way for improved access to treatments.
According to Leslie Neely, associate professor of educational psychology in the College of Education and Human Development at UTSA and director of CAPRI. “There is a huge load on our clinicians to process information and prepare an intervention for the kid. The AI takes this load off.”
With no known cure for ASD, medical evidence suggests early diagnosis can help improve behavioral health and development in those diagnosed with the condition. While diagnosis and treatment for ASD may prove challenging, experts say the key is to develop treatment plans based on the collection and observation of data specific to the needs of the individual, which may include varying treatments including applied behavioral analysis, occupational therapy, speech therapy, physical therapy, and pharmacological therapy.
“The smart health and behavioral sensing platform will make the recommendation for an intervention based on what we know works best for the child’s profile,” Neely explained. “Then the clinician will implement it. We don’t have to disengage (from interaction) to take data or disengage to evaluate data. We amplify the use of people where it matters.”
UTSA’s smart health and behavioral sensing platform can prove beneficial for outpatient clinics and school settings, and university researchers have already moved forward in the installation of sensors and cameras for testing the AI.