Study Finds Smartwatch Heart Rate Feature Can Monitor COVID-19 Symptoms

A new study published in the journal Cell Reports Medicine discovered that a smartwatch can monitor the progression of COVID-19 symptoms. For the study, researchers at the University of Michigan analyzed the impacts of COVID-19 using six factors derived from heart rate data. After following Michigan students and medical interns across the country, the researchers found new indicators embedded in heart rate which can help identify those infected with the virus and how sick they became. For example, the researchers discovered  that those with COVID exhibited an increase in heart rate per step following the beginning of symptoms and that people with coughs had significantly higher heart rates per step than those without coughs.

“We found that COVID dampened biological timekeeping signals, changed how your heart rate responds to activity, altered basal heart rate and caused stress signals,” said Daniel Forger, professor of mathematics and research professor of computational medicine and bioinformatics. “What we realized was knowledge of physiology, how the body works and mathematics can help us get more information from these wearables.”

The Intern Health Study, a multisite cohort study that tracks doctors across many institutes throughout their first year of residency, was employed to select participants from the 2019 and 2020 cohorts. Researchers likewise utilized data from the Roadmap College Student Data Set, a research that incorporated wearable data from Fitbits, self-reported COVID-19 diagnoses and symptom information, and publicly accessible data to analyze students’ health and well-being throughout the 2020–21 academic year. The participants in this analysis were those who reported symptoms, a COVID test that was positive, and wearable data from 50 days before to the beginning of symptoms to 14 days thereafter. The researchers combined data from 72 undergraduate and graduate students and 43 medical interns.

According to the researchers, this study creates algorithms that may be utilized to grasp how diseases affect heart rate physiology and might serve as the foundation for how medical practitioners might utilize wearable technology in healthcare. However, the researchers did note some limitations. For example, they indicate that the work does not consider influenza-like illnesses, along with other factors such as age, gender, and BMI.