BME PhD Preliminary Exam Announcement for Sarwat Amin (M. Ward, advisor) Everyone is invited to attend the public presentation beginning at 8:45 AM (ET). Research title: Continuous Tracking of Autonomic Physiology for Personalized Health Management Across the Lifespan Date: Thursday, March 6, 2025 Time: 8:45 AM (ET) Location: MJIS 2001 Thesis committee members: Matthew P. Ward, PhD (Major professor), Craig J. Goergen, PhD, Bartek Rajwa, PhD, Steven R. Steinhubl, PhD Abstract: The autonomic nervous system (ANS) plays a key role in maintaining a steady state of physiology at rest and in coordinating physiological resources to allow the body to function in a wide range of circumstances encountered in everyday life (homeostasis). In the presence of any external physical, psychological, or environmental stressors, the ANS engages compensatory mechanisms to re-establish the baseline state. Digital health technologies (DHT) support real-time, continuous tracking of physiology, such as heart rate and its beat-to-beat variations, respiration, and skin temperature, providing valuable insights into ANS activity, but importantly without much contextual information to facilitate interpretation of the natural or abnormal patterns of physiological change. DHT-derived physiological metrics exhibit a natural 24-hour pattern that is specific to an individual and their daily activity, lifestyle, location, genetics, and other factors. The Digital Continuous Autonomic Physiologist (dCAP) is a novel multimodal solution designed to monitor and analyze individual autonomic physiology in real-world settings, including the ability to define a normal baseline state and normal pattern of variance in data with respect to circadian clocks and contextual information like environment, nature of scheduled activity, and circumstances of the activity. The dCAP method enables continuous calculation and updating of individualized baselines for physiological signals measured by wearable devices. Through this method, we introduce the 'Annular Baseline' - a dynamic and personalized approach to define a stable baseline accounting for circadian fluctuations and other contextual information unique to the individual. The system has been evaluated with different doses of the COVID-19 vaccine, demonstrating effective detection of deviations from the pre-vaccine baseline across different doses and types of vaccine. This enables early detection of physiological change indicative of the intended inflammatory and immunogenic response to the vaccine. Firstly, we detail the analytical framework of dCAP method and report the performance of DHT-derived physiological signals and different measures of heart rate variability with the help of annular baseline in context of vaccine-induced inflammation. Secondly, we investigate the optimum number of days to establish a stable individualized baseline by analyzing interdaily stability and intradaily variability using electrocardiography data from a cohort of 1738 participants. And thirdly, we detail a plan to validate dCAP’s ability to detect inflammation-related physiological changes using a dataset from an intravenous lipopolysaccharide challenge by investigating the association of onset, duration and trends in changes in DHT-derived metrics with blood biomarkers of inflammation. -- Bmeroundtable-list mailing list Bmeroundtable-list@ecn.purdue.edu https://engineering.purdue.edu/ECN/mailman/listinfo/bmeroundtable-list