Stanford and Fitbit are joining forces in a bid to develop technology that detects early signs of the coronavirus using wearables.
The team is designing an algorithm that measures the wearer’s vitals such as heart rate and skin temperature to determine if the body is fighting an infection.
The software will be capable of spotting unusual patterns, allowing it to predict if the user has contracted an illness before they show physical symptoms.
Stanford Medicine researchers have partnered with Fitbit and Scripps Researcher to roll out the technology in bid to help treat illnesses, such as the coronavirus, before the wearer’s symptoms become apparent.
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Stanford and Fitbit are joining forces in a bid to develop technology that detects early signs of the coronavirus using wearables. The team is designing an algorithm that measures the wearer’s vitals such as heart rate and skin temperature to determine if the body is fighting an infection
Michael Snyder, PhD, professor and chair of genetics at the Stanford School of Medicine, said: ‘Smartwatches and other wearables make many, many measurements per day — at least 250,000, which is what makes them such powerful monitoring devices.’
‘My lab wants to harness that data and see if we can identify who’s becoming ill as early as possible — potentially before they even know they’re sick.’
Fibit is set to invite users to participate in the researcher in order to help train the algorithm to spot signs of an infection.
For this study, Snyder will gather data from five different wearable devices, including smart rings and other smartwatch brands. Those participating in the researcher will be asked to fill out surveys that track their health status
And the Google-owned firm will also provide researchers with 1,000 smartwatches for the project.
As part of this collaboration, scientists at Scripps Research will also work with Fitbit to try to track how infection spreads in a community.
The team hopes that by collecting data from thousands of users, the algorithm will ultimately help people monitor their health by alerting them when their heart rate, skin temperature or some other part of their physiology signals that their body is fighting an infection.
‘You might wonder, “Are these sniffles allergies, or am I getting sick?” These algorithms could help people determine if they should stay home in case their body is fighting off an infection,’ Snyder said.
For this study, Snyder will gather data from five different wearable devices, including smart rings and other smartwatch brands.
Those participating in the researcher will be asked to fill out surveys that track their health status.
Altogether, the group will design five algorithms tailored to each different wearable.
The coronavirus began in Wuhan, China December 2019 and has infected nearly every country in the world. However, the US has been hit the hardest with over 588,000 cases and more than 23,000 deaths reported
But Snyder notes that the timeline of developing the technology will greatly depend on the number of people who sign up for the study.
Although using algorithms to monitor the wearer’s health could be valuable, Snyder has acknowledged there will be obstacles.
‘It’s possible that the algorithms could detect an elevated heart rate, but the user could be watching a scary movie or participating in some other activity that naturally elevates heart rate,’ he said.
‘An alert isn’t a direct diagnosis, and it will be important for folks to be able to contextualize their situation and use some common sense.’
Snyder also adds that even as his team works to develop algorithms that can flag illness, the next step is to investigate whether those signals can be sorted to be able to differentiate between viruses.
The coronavirus began in Wuhan, China December 2019 and has infected nearly every country in the world.
However, the US has been hit the hardest with over 588,000 cases and more than 23,000 deaths reported.
And Stanford and its team hopes their algorithms could help limit the spread and curb the number of deaths by detecting the virus and other infections before the person takes a turn for the worst.