Smartwatches could help detect COVID-19 before symptoms appear: Study

They found that 26 of them (81 per cent) had alterations in their heart rate, number of daily steps or time asleep.
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Smartwatches and other wearable devices that continuously measure vital signs can detect changes in the body up to nine days before COVID-19 symptoms appear, according to a study.

The researchers from Stanford University School of Medicine in the US analysed data from 32 individuals infected with COVID-19, identified from a group of nearly 5,300 participants.

They found that 26 of them (81 per cent) had alterations in their heart rate, number of daily steps or time asleep.

The study, published in the journal Nature Biomedical Engineering, found that for 22 cases they were able to detect changes before or at symptom onset, with four cases detected at least nine days earlier.

The findings suggest that activity tracking and health monitoring via smartwatches and similar devices may be used for the large-scale, real-time detection of respiratory infections.

Early detection of infectious disease is important to mitigate the spread of disease by increasing self-isolation and early treatments, the researchers said.

Presently, 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," the study authors said.

"Moreover, they cannot be implemented routinely at low cost and are constrained by emerging shortages in key reagents," they said.

The researchers noted that 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.

They investigated the use of wearable devices for the early detection of COVID-19 in a retrospective manner, and also present an approach for using wearable device-detected physiological parameters for real-time health monitoring and surveillance.

"Using heart rate and steps data from a large cohort of 5,262 individuals, we show that heart rate signals from fitness trackers can be used to retrospectively detect COVID-19 infection well in advance of symptom onset," the authors said.

"In addition, we developed an online detection algorithm to identify early stages of infection by real-time heart rate monitoring," they said.

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