Project Personalized Digital Biomarker Discovery Platform for the Ehlers-Danlos Syndromes Program DUIRI - Discovery Undergraduate Interdisciplinary Research Internship Term Summer 2025 Status Accepted Research Area Engineering, medicine/physiology, and computer science Description Hypermobile Ehler-Danlos Syndrome (hEDS) is a genetic connective tissue disorder that impacts people globally and leads to a wide range of physical symptoms. A significant aspect of hEDS is its association with dysfunction of the autonomic nervous system (ANS), resulting in symptoms such as fainting, dizziness, and irregular heart rates. The majority of hEDS patients have postural orthostatic tachycardia syndrome (POTS), an abnormal increase in heart rate with postural changes. Each hEDS patient's POTS frequency and severity vary heavily, resulting in inadequate disease management with current healthcare standards. This variability in POTS presentation is further complicated by individual autonomic-altering medication regimens. The variability in patients emphasizes the need for personalized treatments that consider the differing physiological responses. To better understand the individual POTS pathology of hEDS patients, metrics, including heart rate variability, sleep times, heart rate, and temperature, were collected continuously for 30 days utilizing a Corsono CardioWatch. The next step in this research is to develop an algorithm to analyze these physiological responses after postural change. The algorithm will define when a patient rises from the bed as the reference postural change, assuming the patient goes from supine in bed to standing. Utilizing the algorithm, comparisons will be made between hEDS patients and healthy controls, observing patterns and degree of heart rate changes while investigating medication influence. With the knowledge collected from this study, progress toward more personalized treatments for this patient population can be made. Supervisor Matthew Peter Ward Mentor Type of work required Algorithm development for use with digital health technologies; Assist with data collection from patients at University Hospital (Indianapolis, IN); Collaborate with physicians, engineers, and patient advocates; Contribute to scholarly publications and conference presentations Websites Qualifications 1. Experience working with digital health technology derived data streams 2. Intermediate to advanced programming experience 3. Strong foundation in mathematics 4. Creative problem solver Credit Hours 0 Weekly Hours 40 (estimated)