Algorithm Predicts Onset of COVID-19 Symptoms from Data Collected by Wearable Smart Ring

Researchers are developing an algorithm to predict the onset of COVID-19 symptoms based on data collected by a wearable smartring that could also be applied to data from other wearable devices.

The UCSF Osher Center for Integrative Medicine (San Francisco, CA, USA) has been awarded USD 5.1 million by the Medical Technology Enterprise Consortium in partnership with the Department of Defense to expand a study called TemPredict. The research study aims to observe associations between dermal body temperature, heart rate and related metrics, and onset of symptoms such as fever, cough, and fatigue, which can characterize COVID-19. The purpose of this study is to collect information from a wearable sensor that may allow researchers to develop an algorithm that can predict onset of symptoms such as fever, cough, and fatigue, which can characterize COVID-19.

The study uses an Oura Ring which is a wearable device that measures heart rate, inter-beat interval and changes in dermal temperature and is associated with a smartphone app. The researchers are testing whether physiological data collected by the Oura Ring, combined with responses to daily symptom surveys, can predict illness symptoms. The study aims to build an algorithm to identify patterns of, onset of, progression of, and recovery from, COVID-19.

The TemPredict study includes two groups: front-line healthcare workers and the general population. First, TemPredict has provided Oura Rings to more than 3,400 frontline responders, including doctors, nurses, paramedics, and others, who are in daily contact with patients who may be afflicted with COVID-19. Second, the study is open to all Oura Ring users. Through daily symptom surveys, study participants directly contribute their own observations, paired to their Oura data, to the research team. Researchers will use this information as they attempt to identify patterns that could predict onset, progression, and recovery in future cases of COVID-19. If this approach is successful, it could open the door for research into tracking and managing other illnesses and conditions.

TemPredict has gained momentum with over 65,000 participants and ongoing funding awards. In the past several months, TemPredict received funding from #startsmall and more recently, an USD 800,000 contract from the Department of Defense, to collect dried blood samples for COVID-19 antibody testing. Oura seeded the project in March by providing startup funds and 1,400 rings for healthcare workers. The TemPredict study has received the latest award of USD 5.1 million from the Department of Defense to complete antibody testing for 10,000 participants and provide additional support for algorithm development and testing in real-world settings. The pilot testing will allow participants who opt in to receive directives to get tested for COVID-19 based on algorithms using their smartring data. This part of the study will allow the researchers to iteratively test and improve the algorithm and evaluate how it works in the real world.

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UCSF Osher Center for Integrative Medicine