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Portable Fitness Trackers Can Detect COVID Before You Do


30 Nov. 2021 – Your smartwatch or fitness tracker lets you know how many steps you took, how much sleep you got and what your highlight was heartbeat was during that morning workout. What if it can tell you when you are infected with COVID-19 before you notice any symptoms?

This is exactly what a group of researchers hoped would happen when they tested a real-time COVID-19 infection alert system that relied on the data that smartwatches and activity monitor portable devices can collect. The system they built detected 80% of pre-symptomatic and asymptomatic infections, according to a recent study published in Physical Medicine.

The study involved more than 3,300 adults between the ages of 18-80 who installed the researchers’ application, called MyPHD, on their Android or Apple devices. The application collected data from the portable devices they already had and transferred it to a secure cloud server where the researchers could analyze the data. The portable items included Fitbits, Apple Watches, Garmin devices, and other devices that were compatible with either Apple’s HealthKit or Google Fit platforms.

The scientists used an algorithm to look for variations in participants’ step count, heart rate and sleep patterns. If the algorithm detected a measurement outside the expected normal range suggesting a physical stressor, it sent an alert to the carrier. Participants who received a warning then answered several questions about whether they had taken a COVID-19 test, their activity level, any symptoms, medication, and vaccination status. The application made no medical recommendations on isolation or to be tested.

During the study, from November 2020 to July 2021, more than 2,100 participants received real-time alerts daily, and more than 2,100 completed at least one survey. Of the 278 people who reported receiving a positive COVID-19 test, 84 participants (all a Fitbit or Apple Watch) had enough data around the time they had an infection to receive alerts. .

Three days in advance

Sixty-seven of these people received warnings suggesting the potential for infection. The warnings detected an abnormal reading a median 3 days before the person developed symptoms.

Warning signals were even linked to 14 of the 18 cases with a positive test result but no symptoms. Furthermore, the algorithm can detect physical changes that people have had as a result of receiving a COVID-19 vaccine.

Despite the application’s success in identifying abnormal readings linked to infections, many warnings were issued that were not linked to infections.

“Most of the annotated warnings can be attributed to other events, such as poor sleep, stress, alcohol consumption, intense exercise, travel or other activities, “the researchers pointed out.

But there are also situations where the person probably already knows why the reading was abnormal, so they would not worry that they might have an infection, the authors suggested. Although the study lasted less than a year, participants said they did not get tired of the warnings. The researchers plan to refine their application so users can adjust the sensitivity of readings that trigger an alert.



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