The U.S. National Institute on Alcohol Abuse and Alcoholism (NIAAA) awarded a 5-year, $1,373,036 Project Grant (CFDA 93.273 - Alcohol Research Programs) to Yale University. The overarching goal is to enhance understanding and prediction of heavy drinking episodes during initial recovery from alcohol use disorder (AUD) by leveraging wearable biosensors and artificial intelligence (AI) methodologies. The project has two primary aims: 1) Develop real-time predictive models using wearable sensor data to accurately forecast heavy drinking episodes during AUD recovery, and 2) Identify the neuroclinical and physiological mechanisms contributing to or mitigating shifts toward heavy drinking. The research will integrate data from electrocardiograms, transdermal alcohol sensors, self-reports, and behavioral assessments to construct comprehensive profiles for anticipating drinking risk periods. The project brings together experts in AUD treatment, wearable biosensor technology, and AI/computational methods to provide a multifaceted perspective and innovative solutions for improving our understanding and management of AUD recovery.
Generated 3/4/25, 8:13 AM