Early Detection of COVID-19 Using Unobtrusive, Wearable Sensor Data

Led by Deniz S. Ones, Hellervik Professor of Industrial Psychology and Distinguished McKnight University Professor, Department of Psychology; and Michael Cullen, Director of Evaluation, Graduate Medical Education, this study will test the hypothesis that data from an unobtrusive, wearable ring sensor that measures body temperature, heart rate, respiration, sleep quality, and psychological readiness can be useful for early detection of COVID-19, as well as for understanding the consequences of infection indicators for psychological resilience and job performance. The study's researchers have experience studying wellbeing with wearable technologies. "Data from this ring wearable can predict illness reliably, often before users feel unwell," said Ones. "Better understanding COVID-19 contraction, development, and resolution not only helps address the immediate health crisis but helps us better understand impacts on psychological resilience and work performance, preparing the healthcare workforce for potential future similar adverse conditions."