CAIS Seminar: David Eddie (Massachusetts General Hospital) - Towards a biosensor-driven, just-in-time relapse prevention tool for substance use disorder: Identifying neurocardiac biomarkers of stress and relapse risk
Mon, Apr 04, 2022 @ 11:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: David Eddie, Massachusetts General Hospital
Talk Title: Towards a biosensor-driven, just-in-time relapse prevention tool for substance use disorder: Identifying neurocardiac biomarkers of stress and relapse risk
Series: USC Center for Artificial Intelligence in Society (CAIS) Seminar Series
Abstract: Substance use disorders carry tremendous personal and societal costs, and despite best patient and clinical efforts, relapse is common. Much research has sought to identify psychosocial risk factors for addiction relapse, but much less attention has been paid to how psychophysiological impairment may confer risk. In this talk, I will highlight how stress and central autonomic network dysregulation reflected by reduced heart rate variability (HRV) may heighten risk for individuals in early alcohol use disorder (AUD) recovery, showing that HRV can be used to predict subsequent alcohol use. I will also show preliminary findings from a study that aims to use smartwatches and machine learning to identify stress states, with the goal of developing a just-in-time relapse prevention tool for individuals in early recovery from substance use disorder.
Register in advance for this webinar at:
After registering, attendees will receive a confirmation email containing information about joining the webinar.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: David Eddie, Ph.D. is a research scientist at Massachusetts General Hospital\'s Recovery Research Institute and Center for Addiction Medicine, a clinical psychologist in Massachusetts General Hospital\'s Department of Psychiatry, and an assistant professor at Harvard Medical School. His current projects include an NIAAA supported study developing a biosensor driven just-in-time intervention for substance use disorders, and a NIDA supported project assessing the efficacy of a novel mutual-help addiction recovery program based on physical activity.
Host: USC Center for Artificial Intelligence in Society (CAIS)
Location: Online - Zoom Webinar
Audiences: Everyone Is Invited
Contact: Computer Science Department