Sunday, June 26, 2022

Fertility tracker to identify Covid days before symptoms appear

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A wrist-worn health tracker, typically used to monitor fertility, could be used to diagnose a Covid-19 infection days before symptoms appear, new research suggests.

Combined with artificial intelligence (AI), the tracker captures changes in skin temperature, heart and breathing rates, blood flow, and amount and quality of sleep to determine if a person has been infected with the coronavirus.

According to the study, which followed 1,163 people under the age of 51 since the start of the pandemic, 68 percent of Covid cases were successfully diagnosed two days before symptoms appeared.

There is hope that faster diagnosis of Covid-19 could facilitate early isolation and help limit the spread of the virus.

Researchers tested the AVA bracelet, a fertility tracker people can buy online to track the best time to conceive, and wanted to see if physiological changes monitored by the tracker could help develop a machine-learning algorithm to identify them an infection could be used .

Study participants were asked to wear the AVA wristband at night, with the device recording 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.

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

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

The study, published in the journal BMJ Open, found that there were significant changes in the body during the incubation period of infection, the time before symptoms appeared, the time symptoms appeared, and during recovery compared to when it was not infected.

Overall, the tracker and computer algorithm identified 68 percent of Covid-19 positive people two days before their symptoms appeared.

The team, including those from the Cardiovascular Research Institute of Basel, concluded the research had limitations, including not capturing all Covid cases.

However, they added: “Wearable sensor technology can enable detection of Covid-19 during the pre-symptomatic period.

“Wearable sensor technology is an easy-to-use, cost-effective way for 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.”

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

While a PCR test remains the gold standard for confirming Covid infection, “our results suggest that a portable machine learning algorithm could be a promising tool for presymptomatic or asymptomatic detection of Covid-19,” the authors wrote .

“These devices, together with artificial intelligence, can push the boundaries of personalized medicine and detect diseases in advance [symptom occurrence]potentially reducing virus transmission in communities.”

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