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Can smartwatches help detect Covid-19? Here's what this research claims

With the pandemic still not over, focus has now turned whether such wearable devices could detect changes indicating a coronavirus infection.

Published on: Oct 4, 2022, 14:04:38 IST
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Can gadgets like smartwatches detect and track a contagious disease like the Covid-19? With the pandemic still not over, focus has now turned whether such wearable devices could detect changes indicating a coronavirus infection.

An increased breathing rate has turned out to be a biomarker for the early detection of the Covid-19 infection. The breathing rates are estimated through a method called photoplethysmography which only needs a single point of contact, an article published in online journal The Conversation stated.

The method is susceptible to light, pressure or motion. As a result, most of the studies seeking to use this method to detect the coronavirus infection focused on monitoring people during sleep.

An increased breathing rate has turned out to be a biomarker for the early detection of the Covid-19 infection (Representative image/Pexels)
An increased breathing rate has turned out to be a biomarker for the early detection of the Covid-19 infection (Representative image/Pexels)

Smartwatch maker Fitbit analysed the nocturnal breathing rates of thousands of users of their devices to analyse whether this process could aid Covid detection. They found that within a week period, a portion of people with Covid showed at least one measurement of increased breathing rate, the report by University of Essex senior lecturer Javier Andreu-Perez stated.

The report stated that this was detected in one-third of symptomatic patients, and one-quarter of asymptomatic patients. The study suggested that commercial wearable devices could be a non-invasive way to detect possible infections.

Another study analysed the potential of a US brand WHOOP's fitness tracker. The data on respiratory rate and other indicators of heart function from a group of Covid patients was used to predict infection.

This model was tested on a separate group of Covid-19 patients and others without the infection, but having similar symptoms. As per the respiratory rate during the sleep, the tracker was able to identify 20 per cent of Covid-19 positive cases in the two days before symptom onset, and 80 per cent by the third day of symptoms.

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