Health trackers worn on the wrist can help detect COVID-19 days before the first telltale signs of the viral illness appear, according to a study. The researchers noted that an increasing number of people around the world are using health trackers to monitor changes in skin temperature, heart rate and respiratory rate.
The latest study, published in the journal BMJ open, shows that this data could be combined with artificial intelligence (AI) to diagnose COVID-19 even before any symptoms appear. While a swab PCR test remains the gold standard for confirming COVID-19, “our results suggest that a wearable-informed machine learning algorithm may serve as a promising tool for presymptomatic or asymptomatic detection of COVID-19. COVID-19,” the researchers said.
Researchers, including those at the Risch Medical Laboratory, Liechtenstein, base their findings on AVA bracelet wearers. The regulated, commercially available fertility tracker monitors respiratory rate, heart rate, heart rate variability, wrist skin temperature and blood flow, as well as sleep quantity and quality.
Typical symptoms of COVID-19 may take several days after infection to appear, during which time an infected person may unwittingly spread the virus. The researchers wanted to see if physiological changes, monitored by an activity tracker, could be used to develop a machine learning algorithm to detect COVID-19 infection before symptoms start.
No less than 1,163 participants under the age of 51 were drawn from the GAPP study between March 2020 and April 2021. GAPP, which began in 2010, aims to better understand the development of cardiovascular risk factors in the general population of the Liechtenstein. Participants wore the AVA Bracelet at night. The device records data every 10 seconds and requires at least four hours of relatively uninterrupted sleep. The bracelets were synchronized with a complementary smartphone application upon waking. They regularly took rapid antibody tests for SARS-CoV-2, the virus responsible for COVID-19 infection. Those with indicative symptoms also had a PCR swab test. Some 127 people (11%) developed COVID-19 infection during the study period. Among them, 66 (52%) had worn their bracelet for at least 29 days before the onset of symptoms and were confirmed positive by the PCR swab test, so they were included in the final analysis.
Surveillance data revealed significant changes in all five physiological indicators during the incubation, pre-symptomatic, symptomatic, and recovery periods of COVID-19 compared to baseline measurements. Symptoms of COVID-19 lasted an average of 8.5 days. The algorithm was “trained” using 70% of data from day 10 to day 2 before symptom onset during a 40-day continuous surveillance period of the 66 people who tested positive for SARS-CoV-2. It was then tested on the remaining 30% of the data. Some 73% of lab-confirmed positive cases were detected in the training set and 68% in the testing set, up to two days before symptoms began.
“Wearable sensor technology is an easy-to-use, low-cost method for individuals to track their health and well-being during a pandemic,” the researchers said. “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 transmission of the virus in communities,” they said. declared.
The researchers acknowledge that their findings may not be more widely applicable. The results were based on a small sample of people, all of whom were relatively young – so less likely to have severe COVID-19 symptoms – from a single national center, and who were not ethnically diverse, they said. The precision (sensitivity) obtained was less than 80%. But the algorithm is currently being tested on a much larger group (20,000) of people in the Netherlands, with results expected later this year, the researchers added.
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