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Smartwatches Could Detect Early Signs of COVID-19

by Dr. Hena Mariam on November 23, 2022 at 12:50 PM
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Highlights:

A recent study showed that resting heart rate data from smartwatches could be used to detect the early signs of COVID-19 infection (1).


Early detection of infectious disease is important to mitigate the spread of disease by increasing self-isolation and early treatments. Most diagnostic methods involve sampling nasal fluids, saliva or blood, followed by nucleic acid-based tests for detecting active infections or blood-based serological detection for past infections. Although they are highly sensitive, nucleic acid-based diagnostics may require samples gathered several days post-exposure for unambiguous positive detection (2). Moreover, they cannot be implemented routinely at low cost and are constrained by emerging shortages in key reagents.

‘Wearable devices can help detect early symptoms of COVID-19 making it convenient for people to practice caution and self-isolate.’

Consumer wearable devices are an accurate and widely deployed technology to establish individual baseline parameters of health, which may be used to detect substantial deviations from baseline physiology at the onset of infection (3).

The use of wearable devices has ample potential to mitigate the coronavirus disease 2019 (COVID-19) pandemic. To date, the pandemic has infected tens of millions of individuals and caused over one million deaths worldwide (4). There is a substantial need for improved infection tracking, and population-scale technology solutions provide a promising avenue to identify cases in real time for infection detection and tracking (5).

Smartwatches and other wearable devices are already used by tens of millions of people worldwide and measure many physiological parameters, such as heart rate, skin temperature and sleep (6).

Data from Smartwatches can Detect Early Symptoms of COVID-19

The data from consumer smartwatches can be used for the pre-symptomatic detection of COVID-19. Analysis of physiological and activity data from 32 individuals infected with COVID-19, identified from a cohort of nearly 5,300 participants, it was found that 26 of them (81%) had alterations in their heart rate, number of daily steps or time asleep. Of the 25 cases of COVID-19 with detected physiological alterations for which had symptom information, 22 were detected before (or at) symptom onset, with four cases detected at least nine days earlier. Using retrospective smartwatch data, it is shown that 63% of the COVID-19 cases could have been detected before symptom onset in real time via a two-tiered warning system based on the occurrence of extreme elevations in resting heart rate relative to the individual baseline. The findings suggest that activity tracking and health monitoring via consumer wearable devices may be used for the large-scale, real-time detection of respiratory infections, often pre-symptomatically.

References:
  1. Pre-symptomatic detection of COVID-19 from smartwatch data - (https:www.nature.com/articles/s41551-020-00640-6)
  2. Interpreting Diagnostic Tests for SARS-CoV-2 - (https:pubmed.ncbi.nlm.nih.gov/32374370/)
  3. Wearables and the medical revolution - (https:pubmed.ncbi.nlm.nih.gov/30259801/)
  4. WHO Coronavirus (COVID-19) Dashboard - (https:covid19.who.int)
  5. Wearable Sensors for COVID-19: A Call to Action to Harness Our Digital Infrastructure for Remote Patient Monitoring and Virtual Assessments - (https:pubmed.ncbi.nlm.nih.gov/34713021/)
  6. Windows Into Human Health Through Wearables Data Analytics - (https:pubmed.ncbi.nlm.nih.gov/31832566/)


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