Trackers worn on wrist can detect Covid before symptoms, study finds | Coronavirus

Wrist-worn health trackers could be used to detect Covid-19 days before symptoms appear, researchers say.

More and more people around the world are using the devices to monitor changes in skin temperature, heart rate and respiratory rate. Now a new study shows that this data could be combined with artificial intelligence (AI) to diagnose Covid-19 even before the first telltale signs of the disease appear.

“Wearable sensor technology may enable detection of Covid-19 during the pre-symptomatic period,” the researchers concluded. The results were published in the journal BMJ Open.

The discovery could lead to health trackers being adapted with AI to detect Covid-19 early, simply by detecting fundamental physiological changes. This could help provide users with an early warning system that they may be infected, which in turn may help prevent further spread of the disease.

researchers of the dr. Risch Medical Laboratory in Liechtenstein, the University of Basel in Switzerland, McMaster University in Canada and Imperial College London tested the Ava bracelet, a fertility tracker people can buy online to track the best time to conceive. It monitors respiratory rate, heart rate, heart rate variability, wrist skin temperature and blood flow.

In the study, 1,163 people under the age of 51 were observed in Liechtenstein from the beginning of the pandemic until April 2021. They were asked to wear the Ava bracelet at night with the device, which costs £249 and stores data every 10 seconds. Humans need to sleep at least four hours for it to work.

The wristbands were synced to a smartphone app, with people recording any activities that might impact results, such as: such as alcohol, prescription drugs, and recreational drugs. They also recorded possible Covid 19 symptoms such as fever.

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All participants in the study underwent regular rapid antibody testing for Covid-19, while those with symptoms also underwent a PCR swab test.

A total of 1.5 million hours of physiological data was recorded and Covid-19 was confirmed in 127 people, of whom 66 (52%) had worn their device for at least 29 consecutive days and were included in the analysis.

The study found that there were significant changes in the body during the incubation period of infection, the period before symptoms appeared, the period when symptoms appeared, and during recovery compared to non-infection.

Overall, the dual combination of health tracker and computer algorithm correctly identified 68% of Covid-19 positive people two days before their symptoms appeared. The team pointed out that the research has limitations, including not recording all Covid cases.

While a PCR swab test remains the gold standard for confirming Covid-19, “the results suggest that a wearable-informed machine learning algorithm could serve as a promising tool for presymptomatic or asymptomatic detection of Covid-19,” the researchers said .

They added: “Wearable sensor technology is an easy-to-use, cost-effective way to enable individuals to track their health and well-being during a pandemic.

“Our research shows how these devices, combined with artificial intelligence, can push the boundaries of personalized medicine and detect diseases before symptoms appear, potentially reducing virus transmission in communities.”

Typical Covid-19 symptoms can take several days after infection to appear, during which time an infected person can unknowingly spread the virus.

The algorithm is now being tested on a much larger group of 20,000 people in the Netherlands, with results expected later this year.

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