Wearable devices have long been capable of monitoring more than just fitness metrics. Research from the University of Michigan explains how your smartwatch can now also monitor symptoms of Covid.
The researchers identified six factors derived from heart rate data that can determine the effects of Covid. What’s more, the team believes that it could also be used to detect other illnesses, such as influenza. For instance, they found that people with Covid tend to have an increase in their heart rate per step.
“We found that COVID dampened biological timekeeping signals, changed how your heart rate responds to activity, altered basal heart rate and caused stress signals,” the researchers explain. “What we realized was knowledge of physiology, how the body works and mathematics can help us get more information from these wearables.”
Spotting symptoms
The analysis found that these various measures were usually significantly altered and could therefore highlight both symptomatic and healthy periods in the lives of the wearer.
“There’s been some previous work on understanding disease through wearable heart rate data, but I think we really take a different approach by focusing on decomposing the heart rate signal into multiple different components to take a multidimensional view of heart rate,” the authors say.
“All of these components are based on different physiological systems. This really gives us additional information about disease progression and understanding how disease impacts these different physiological systems over time.”
Tracking disease
The researchers recruited volunteers from the Intern Health Study, which tracks physicians during their first year of residency alongside information from the Roadmap College Student Data Set, which examines student health during the 2020-2021 academic year using wearable data from Fitbit devices as well as self-reported Covid information.
They were particularly interested in those who had a confirmed positive Covid test and wearable data for a full 50 days prior to the test and 14 days after it. They found that heart rate commonly increased per step, which is a sign of cardiopulmonary dysfunction. This was especially so for those who also reported a cough.
What’s more, they also observed considerable circadian phase uncertainty, which is when our body struggles to time daily events. Similarly, our daily basal heart rate also increased on or even before the onset of symptoms, with the researchers hypothesizing that this could be due to fever or even anxiety.
The findings emerged after the use of an AI algorithm that had originally been developed to track the daily circadian phase from wearable heart and step monitors. They hope that this approach could ultimately be used to improve our ability to detect Covid from wearable data.
“The global outbreak of the SARS-CoV-2 virus imposed important public health measures, which impacted our daily lives,” the researchers explain. “However, during this historical event in time, mobile technology offered enormous capabilities—the ability to monitor and collect physiological data longitudinally from individuals noninvasively and remotely.”
They hope that the study also highlights the crucial role algorithms can play in helping us to better understand the impact illnesses have on our heart rate physiology, which can ultimately lead to the deployment of wearables in other areas of healthcare.
“Identifying the varying patterns of different heart rate parameters derived from wearables across the course of COVID-19 infection is a substantial advance for the field,” the researchers conclude. “This work can help us more meaningfully follow populations in future COVID-19 waves. The study also demonstrates following cohorts with mobile technology and robust data sharing can facilitate unanticipated and valuable discoveries.”
