Apple Watch Could Spot You’re Sick With Covid-19 Before You Do

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Apple Watch has always put health front-and-center, and Fitbit went so far as to allude to fitness in its name. Now, as reported by ZDNet, Stanford University has launched the Coronavirus Wearables Study to find out if it’s possible for the watches and trackers we have about our person most of the time can be used to predict Covid-19 even before symptoms develop.

This predictive approach is rumored to be part of other Apple Watch improvements expected to arrive in the coming months or years. One report claims that by recognizing the way a wearer’s body changes in the run-up to a panic attack, the Watch can issue a warning before it happens, to help head it off.

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The study will ask participants to share data including heart rate, skin temperature and blood oxygen saturation. Not every wearable can measure all of these – Apple has never implemented blood oxygen saturation monitoring, and will likely need a hardware upgrade to do so.

Once collected, the data will be used to create algorithms designed to spot physiological changes that happen to the wearer and indicate sickness is on the way. These changes involve a higher resting heart rate, for instance. The app can then warn the wearer with an alert that they may be getting ill.

Why this is so important with Covid-19 is that if someone self-isolates sooner than they otherwise would have, the prospect of spreading the virus to someone else is reduced.

Previous research at Stanford showed that devices could pick up changes in physical parameters, often noticing the changes before the wearer did. In that case, the study was dealing with changes in heart rates which could signal an early stage of infection, and this 2017 study has been used to improve the algorithm for spotting Covid-19. Michael Snyder, Professor and Chair of Genetics at Stanford School of Medicine explained that when the outbreak began the team “started scaling at full force”.

All of which is interesting enough but it seems to be yielding useful results. Snyder says that the first case the lab looked into was able, through the wearable, to detect physiological changes that indicated an infection. Strikingly, it did this more than nine days before the symptoms appeared. Snyder told ZDNet, “You can’t miss the signal. It’s very, very clear. That person is running around for nine and a half days ill, asymptomatic and not knowing it, therefore presumably infecting many others.”

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