Wearables watch out for COVID-19 through heart rate variability

Using a commonly available wearable device to measure changes in heart rate variability (HRV) may help detect the novel coronavirus disease (COVID-19), according to a recent study.

“[W]e demonstrated a relationship between longitudinally collected HRV acquired from a commonly used wearable device and SARS-CoV-2 infection. These preliminary results support the further evaluation of HRV as a biomarker of SARS-CoV-2 infection by remote sensing means,” the researchers said.

The study included 297 healthcare workers (median age, 36 years; 69 percent female). All participants were made to wear an Apple Watch for a minimum of 8 hours per day but were otherwise instructed to go about their activities as per normal. Daily questionnaires were administered to capture COVID-19-related symptoms, as well as swab and antibody test results.

Over a median follow-up of 42 days, 13 participants tested positive for SARS-CoV-2 through a nasal swab; 20 had the same result prior to enrollment. A median of 28 HRV samples were collected per participant. [J Med Internet Res 2021;doi:10.2196/26107]

The researchers observed a significant difference in the mean amplitude of the circadian pattern of the standard deviation of the interbeat interval of normal sinus beats (SDNN) between those who were vs were not diagnosed with COVID-19 (1.23 vs 5.30 ms; p=0.006).

In contrast, the midline statistic of rhythm (MESOR; p=0.46) and acrophase (p=0.80) did not differ between the infection groups. The same findings were obtained when the analysis was repeated, excluding participants who had never been tested.

Differences in HRV were observed in the days before and after COVID-19 diagnosis. For instance, the amplitude of the SDNN circadian rhythm was significantly lowered in infected patients, both in the 7-day period before (0.29 ms; p=0.01) and after (1.22 ms; p=0.01) diagnosis, as opposed to noninfected comparators (5.31 ms). MESOR and acrophase did not differ between infection groups at any time frame.

Wearable device data also showed that HRV factors could help detect COVID-19 symptoms. The mean MESOR of SDNNs circadian pattern was significantly higher during the first day of symptoms than all other days (46.01 vs 43.48 ms; p=0.01). The opposite trend was true for the mean amplitude of SDNNs circadian pattern (2.58 vs 5.30 ms; p=0.01).

“Additionally, most participants diagnosed with COVID-19 in our cohort were asymptomatic,” the researchers said. “We demonstrated that there was no difference in changes in HRV metrics between those with and without symptomatic COVID-19 infections. These findings support the utility of using wearable technology to identify COVID-19 infections even in asymptomatic individuals.”

“While further study is needed, [the current findings] may allow for the identification of SARS-CoV-2 infection during the presymptomatic period, in asymptomatic carriers, and prior to diagnosis by a SARS-CoV-2 nasal [swab] tests,” they added. “These findings warrant further evaluation of this approach to track and identify COVID-19 infections and possibly other type of infections.”