SCC-PG: Bridge: An AI-Enabled Platform to Support Coordinated Care for Children with Autism

University Of Texas At San Antonio, San Antonio TX

Investigators

Abstract

Children with autism spectrum disorder (CWA) often engage in severe problem behavior, and thus require long-term care with individualized clinical assessment, treatment, and intervention. Applied behavior analysis (ABA) therapy, considered an evidence-based best practice, can be time-consuming, resource intensive, and prone to human bias. This Smart and Connected Communities Planning Grant (SCC-PG) project seeks to co-design an AI-based solution for collecting behavior data for automatic measurement of severe behaviors (e.g., frequency, intensity, latency, etc.), assisting diagnosis and treatment decisions, and communicating to patients and families in real-time for early intervention. The project team partners with a range of community stakeholders in a pilot study in San Antonio, TX for coordinated care of CWA through an AI-augmented platform. The planning process begins with identifying key platform parameters including data types, privacy concerns, main function modules, and expected performance. Different AI algorithms are examined for fusing multi-modal data to inform ABA. Post-survey and focus groups are conducted to uncover the effects of incorporating the IoT-Edge-Cloud prototype into clinical practices. The project has the potential to improve health outcomes for autistic children and the well-being of their families. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.