Mount Sinai: Apple Watches spot heart rate variability changes prior to COVID-19 diagnosis

New research suggests that the wearable could help identify COVID-19 cases up to seven days before a positive diagnostic test.
By Dave Muoio
02:03 pm

Mount Sinai researchers are the latest to share data indicating that consumer wearable devices can help flag new cases of COVID-19 prior to molecular diagnosis.

Accepted for publication in the Journal of Medical Internet Research, the institution's Warrior Watch Study provided Mount Sinai Health System workers with an Apple Watch and a custom study app. The results highlight a significant differences in a heart rate variability (HRV) metric during the seven days before a PCR COVID-19 diagnosis and the seven days after.

"[This study] shows that we can use these technologies to better address evolving health needs, which will hopefully help us improve the management of disease," Dr. Robert P. Hirten, assistant professor of medicine at the Icahn School of Medicine at Mount Sinai and the study's corresponding author, said in a statement. "Our goal is to operationalize these platforms to improve the health of our patients and this study is a significant step in that direction. Developing a way to identify people who might be sick even before they know they are infected would be a breakthrough in the management of COVID-19."


The final dataset included 297 participants who completed a median follow-up of 42 days. The median age upon enrollment was 36 years, and 69% were women. Prior to enrollment, 20 participants reported a positive COVID-19 nasal PCR test before enrollment, while 28 reported a positive COVID-19 blood antibody test. Thirteen participants reported a positive PCR test within the study's follow-up period.

There was a significant difference in the mean amplitude of the standard deviation of the interbeat interval of normal sinus beats (SDNN) circadian patterns – a metric of HRV, which is tied to nervous system function – between those with and without COVID-19 (P = .006). These measures also differed when examining the seven-day period prior to a positive COVID-19 diagnosis to uninfected participants' readings (P = .01).

Participants' HRV patterns began to normalize within 7-14 days after a COVID-19 diagnosis. And while most participants in the study cohort were asymptomatic, the researchers said they also observed a significant change in multiple circadian pattern measures when comparing the first day a COVID-19-related symptom was reported to all other days of follow-up.

"This technology allows us not only to track and predict health outcomes, but also to intervene in a timely and remote manner, which is essential during a pandemic that requires people to stay apart," Zahi Fayad, a professor at the Icahn School of Medicine at Mount Sinai and a study coauthor, said in a statement.


Between April 20 and Sept. 29, 2020, the observational study enrolled Mount Sinai healthcare workers who owned an iPhone Series 6 or higher smartphone, and who owned or were willing to wear an Apple Watch Series 4 or higher smartwatch. Those who had an underlying autoimmune disease or were on medications that interfere with autonomic nervous system function were excluded.

These participants completed baseline and daily survey questionnaires through the study's custom app, the latter of which focused on COVID-19 symptoms, diagnostic test results and exposure due to patient care.

During this time, they were also instructed to wear their Apple Watch for at least eight hours per day. The device captured HRV using its onboard photoplethysmogram (PPG) optical heart sensor and transferred the readings to the study app upon daily survey completion. Researchers then analyzed changes in HRV curves to determine any association with COVID-19 diagnosis and symptoms, as well as whether COVID-19 could be predicted using the collected data.


Mount Sinai's wearable study is one of several efforts using wearables to better characterize COVID-19 infection and spot early warning signs of the disease.

Among the most prominent studies has been Scripps Research Translational Institute's DETECT program, which received major support from Fitbit. The wearable maker also headed its own review of user data, the early results from which lend support to early diagnosis of new infections prior to symptom onset (a finding that seems to have drawn the attention of the U.S. Army).

Other projects in this area include a recent paper describing early detection capabilities among study participants wearing the Oura Ring and Evidation Health's ongoing collaboration with the National Institutes of Health that is analyzing wearables data for early COVID-19 warning signs.


"These preliminary results support the further evaluation of HRV as a biomarker of SARS-CoV-2 infection by remote sensing means," the researchers wrote. "While further study is needed, this may allow for the identification of SARS-CoV-2 infection during the pre-symptomatic period, in asymptomatic carriers and prior to diagnosis by a SARS-CoV-2 nasal PCR tests. These findings warrant further evaluation of this approach to track and identify COVID-19 infections and possibly other type of infections."


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