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{"id":4432,"date":"2022-04-26T11:05:29","date_gmt":"2022-04-26T11:05:29","guid":{"rendered":"https:\/\/scienceandnerds.com\/2022\/04\/26\/research-on-covid-detecting-smartwatches-still-hasnt-panned-out\/"},"modified":"2022-04-26T11:05:31","modified_gmt":"2022-04-26T11:05:31","slug":"research-on-covid-detecting-smartwatches-still-hasnt-panned-out","status":"publish","type":"post","link":"https:\/\/scienceandnerds.com\/2022\/04\/26\/research-on-covid-detecting-smartwatches-still-hasnt-panned-out\/","title":{"rendered":"Research on COVID-detecting smartwatches still hasn\u2019t panned out"},"content":{"rendered":"

Source: https:\/\/www.theverge.com\/2022\/4\/25\/23040869\/covid-detecting-smartwatch-illness-fitbit-apple-watch<\/a>
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In the early days of the COVID-19 pandemic, smartwatch advocates and wearable tech companies thought the devices could help with illness detection. They wanted to flag people who might be sick with the disease using things like their heart rate and oxygen levels. The strategy could still be a reasonable way to track illness, but two years later, the promise hasn\u2019t panned out \u2014 the research is still underdeveloped, according to a new review published last week in The Lancet<\/em><\/a>.<\/p>\n

The review looked at 12 research studies and 12 proposed study protocols published in 2020 and 2021 that tried to find patterns in the data collected by devices like the Apple Watch, Fitbit, and Whoop. Most of these studies focused on people who had already tested positive for COVID-19. Researchers looked for patterns in wearable data from the few days before a person got sick, rather than following healthy people and trying to predict who would fall ill. None of the studies were rigorous clinical trials, the authors of this new study noted. None of the existing research tested to see if a wearable device could actually lead to earlier detection of COVID-19. <\/p>\n

Most algorithms built to divine COVID-19 out of wearable data mainly focused on symptomatic disease, the study found. Four tried to detect an infection before a person started to show symptoms, with varying success \u2014 they were able to detect between 20 and 88 percent of infections. The models got less accurate the more days in advance they tried to predict illness. \u201cThe accumulated evidence suggests a trade-off between a model\u2019s accuracy and its ability to identify SARS-CoV-2 infection before symptom onset,\u201d the review authors wrote. That would also make the devices less useful as COVID-19 detectors \u2014 some of the promise of this type of strategy is flagging people who are sick early enough that they can get tested and isolate before they could spread the disease to others.<\/p>\n

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