Explainable AI for Predicting Adverse Behaviors in Autism Spectrum Disorder Using Nonintrusive Sleep Monitoring

Developing AI models that analyze the dynamics of sleep and daytime behavior, this research aims to predict adverse behaviors in individuals with ASD by understanding their underlying physiological and psychological states. In collaboration with the The Center for Discovery, the project seeks to create an open-source tool for proactive interventions, reducing high-risk behaviors and improving care for individuals with ASD.

Related Publications

• Kiarashi, Y., Suresha, P.B., Rad, A.B., Reyna, M.A., Anderson, C., Foster, J., Lantz, J., Villavicencio, T., Hamlin, T. and Clifford, G.D., 2024. Off-body Sleep Analysis for Predicting Adverse Behavior in Individuals with Autism Spectrum Disorder. IEEE Journal of Biomedical and Health Informatics. Link
• Kiarashi, Y., Lantz, J., Reyna, M.A., Anderson, C., Rad, A.B., Foster, J., Villavicencio, T., Hamlin, T. and Clifford, G.D., 2024. Forecasting High-Risk Behavioral and Medical Events in Children with Autism through Analysis of Digital Behavioral Records. medRxiv. Link