Fitbits might be used for predicting the onset of COVID-19
Fitbit has recently added a bunch of features to help protect users of its app from COVID-19. But it hopes to go much further than that. The company is exploring whether its wearables can be used for predicting the onset infectious diseases before symptoms start.
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COVID-19 is on most people’s minds. We are all more cognisent of the need to maintain proper hygene and social distancing measures are in place in many countries.
A few weeks ago Fitbit added a new tab in its smartphone app for users in the UK, the US and Australia. Titled COVID-19, it slaps on tools and resources to help users deal with the pandemic. Amongst these are suggestions on how to stay healthy and happy while stuck indoors, options to connect to doctors online and coronavirus info from the World Health Organization.
But it has now emerged the company hopes to go much further than that. Fitbit reportedly paid $200,000 to secure meetings with members of the Senate, the Department of Health and Human Services, the White house and Donald Trump’s office. The topics of discussion revolved on how its tech can be used to help manage the COVID-19 pandemic.
This included an exchange of views on how Fitbit’s data could be utilized to monitor the spread of COVID-19 amongst the population and inform local policy. Having sold over 100 million devices since its inception, the company currently has around 30 million active users.
Its fitness trackers and smartwatches collect information on everything from steps and distance travelled, to heart rate and detailed sleep statistics. A number of its wearables even monitor blood oxygen levels during the night. A fall in these values might indicate respiratory issues, which often accompany those infected with COVID-19. An increase in resting heart rate can also be an indicator of influenza-like illnesses.
Fitbit data scientists could, potentially, monitor for these signs and alert local officials if they suspect the virus is spreading in their region. The company is currently doing something similar to this in a study with Stanford University and Scripps Research Institute.
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