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Device Technologies and Biomedical Robotics

Device Technologies and Biomedical Robotics - Poster Session C & D

X13 - Wearable Syncope Detection Device

Friday, October 10, 2025

10:00 AM - 11:00 AM PDT

Location: Exhibit Hall F, G & H

Presenting Author(s)

AC

Aaliyah Couto

Undergraduate Student
Johnson & Wales University
Providence, Rhode Island, United States

Co-Author(s)

Nicole H. Urban, PhD

Professor
Johnson & Wales University
Portsmouth, Rhode Island, United States
EP

Emily Patenaude

Undergraduate Student
Johnson & Wales University
Providence, Rhode Island, United States

Introduction: : Syncope (fainting) and presyncope (near-fainting) episodes are unpredictable and challenging to diagnose. Syncope is associated with conditions including postural orthostatic tachycardia syndrome (POTS), aortic stenosis, and arrhythmias, yet for 10-40% of patients, the underlying cause is unknown (1,2). Patients often struggle to recall details of their episodes, such as whether their heart was racing or beating irregularly, whether they had stayed well-hydrated throughout the day, or if they were experiencing elevated stress levels at the time of the episode. These factors can result in delayed or inaccurate diagnoses. The current standard of care generally includes intermittent testing, so key physiological changes occurring in real time, just prior the syncopal episode, can be missed. This results in unnecessary tests and procedures, increased healthcare costs, and prolonged uncertainty for patients. Our technology is a discrete, affordable, and user-friendly wearable device that continuously monitors key physiological data, including skin temperature, heart rate variability, and body position, to provide critical information about the immediate pre-syncopal window to the clinician, to support more rapid and informed diagnoses.

Materials and

Methods: : Commercially available options for health monitoring are generally incorporated into a ring device or a wrist-worn device, such as a smart watch. These can provide a variety of health metrics, complied from continuous wear data, but they are not designed to recognize and analyze syncopal episodes. To address this gap in technology, a discrete, wearable device prototype was developed to provide immediate feedback to the user or care giver about syncopal episodes. The prototype includes a variety of sensors integrated into the inner fabric folds of a headband. This allows for secure mounting of the sensors, microprocessor, LCD screen, and all associated wiring within the fabric, so that it is almost completely hidden from view.
The initial prototype was tested by continuously recording the output of a triple axis accelerometer on the attached LCD screen, to ensure accurate capture of simulated falls. The fall simulations involved attaching the prototype to a mannequin head and rapidly changing the orientation of the mannequin head by 90 degrees, essentially from a vertical to a horizontal orientation. Once simulated falls were consistently and accurately displayed on the LCD screen, additional sensors were incorporated. Initial programming was developed to record and average sensor signals from the 30 seconds prior to the simulated syncopal episode.

Results, Conclusions, and Discussions:: Future work includes testing fall scenarios on a full-size mannequin, to ensure the device is accurately capturing and categorizing types of falls. Two different options for the onboard LCD screen will be offered; a hidden (internal) screen will be incorporated for individual monitoring by the patient and a front-facing (external) screen will be incorporated if the patient is being monitored by a caregiver. A WebApp will be developed to allow the patient or caregiver to download device data for viewing or for distribution to their care team. Temperature, hydration, blood oxygenation, and pulse monitoring sensors will be incorporated to enhance the breadth of health metrics associated with each episode, and testing scenarios will be enhanced to simulate standard variations of these metrics associated with syncopal episodes. For example, textiles with varying moisture levels will be placed adjacent to the hydration and temperature sensors to simulate changes in skin moisture and temperature. Similarly, simulated heart rate signals will be used to test the device's efficacy. Once these scenarios are simulated and data recorded, more complex metrics, including heart rate variability will be calculated and incorporated for display.
Syncope is challenging to diagnose, and new technologies are needed to support more rapid and accurate clinical diagnoses. Further development and testing of this simple, patient-centric, discrete, customizable technology can provide the data needed to facilitate accurate diagnoses by providing critical health metrics from the pre-syncopal window of time.

Acknowledgements and/or References (Optional): : References
1. Kidd, S. K., Doughty, C., & Goldhaber, S. Z. (2016). Syncope (Fainting). Circulation, 133(16), 1604–1609. https://doi.org/10.1161/CIRCULATIONAHA.115.017308.
2. Pallais, J. C., Schlozman, S. C., Puig, A., Purcell, J. J., & Stern, T. A. (2011). Fainting, swooning, and syncope. The Primary Care Companion for CNS Disorders, 13(4). https://doi.org/10.4088/pcc.11f01187.

Research reported in this presentation was supported in part by the Rhode Island Institutional Development Award (IDeA) Network of Biomedical Research Excellence from the National Institute of General Medical Sciences of the National Institutes of Health under grant number P20GM103430.