Wearables can track COVID symptoms, other diseases

Additional uses for fitness wearables

If you become ill with COVID-19, a wearables devise such as a smartwatch can track the progression of your symptoms, and could even show how sick you become.

That’s according to a University of Michigan study that examined the effects of COVID-19 with six factors derived from heart rate data. The same method could be used to detect other diseases such as influenza, and the researchers say the approach could be used to track disease at home or when medical resources are scarce, such as during a pandemic or in developing countries.

Following U-M students and medical interns throughout the country, the researchers discovered new signals embedded in heart rate indicating when individuals were infected with COVID and how sick they became. The researchers found that individuals with COVID experienced an increase in heart rate per step after symptom onset, and those with a cough had a much higher heart rate per step than those without a cough.

“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 researchers found that these measures were significantly altered and could show symptomatic vs. healthy periods in the wearers’ lives.

Participants were drawn from the 2019 and 2020 cohorts of the Intern Health Study, a multisite cohort study that follows physicians across several institutes in their first year of residency. Researchers also used information from the Roadmap College Student Data Set, a study that examined student health and well-being during the 2020-21 academic year using wearable data from Fitbits, self-reported COVID-19 diagnoses and symptom information, and publicly available data.

Related:   Awareness Inspires Preparedness: Educating the Public About Electromagnetic Fields

Specifically, the researchers found:

  • Heart rate increase per step, a measure of cardiopulmonary dysfunction, increased after symptom onset.
  • Heart rate per step was significantly higher in participants who reported a cough.
  • Circadian phase uncertainty, the body’s inability to time daily events, increased around COVID symptom onset. Because this measure relates to the strength and consistency of the circadian component of the heart rate rhythm, this uncertainty may correspond to early signs of infection.
  • Daily basal heart rate tended to increase on or before symptom onset. The researchers hypothesize this was because of fever or heightened anxiety.
  • Heart rate tended to be more correlated around symptom onset, which could indicate the effects of the stress-related hormone adenosine.

The researchers used an algorithm that was originally developed to estimate daily circadian phase from wearable heart rate and step data. They looked at a baseline period of 8-35 days before COVID symptom onset and an analysis period defined as 7-14 days around COVID symptom onset. The researchers hope that with further testing, the same methods could enhance the pre-detection of COVID with wearables.

The researchers say this work establishes algorithms that can be used to understand illnesses’ impact on heart rate physiology, which can form the basis for medical professionals might deploy the use of wearables in health care.

Co-authors of the study also include U-M researchers Jonathan Tyler, Yu Fang, Christopher Flora, Elena Frank and Muneesh Tewari. The work was supported by the National Institutes of Health, Human Frontier Science Program, National Science Foundation and a Taubman Institute Innovation Project grant.

Related:   Do you know how to choose the best comforter? Here you have the keys

Source: University of Michigan

Be the first to comment

Leave a Reply

Your email address will not be published.