Scientists from Stanford Medicine are collaborating with Scripps Research and Fitbit to train a series of algorithms for the early detection of viral infection using data from smartwatches and other wearables. The project will use five different wearables to test five different algortithms and will require many participants for the testing. For its part, Fitbit has donated 1,000 units of its smartwatches and is actively promoting the study to its users to encourage participation.
“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,” Michael Snyder, PhD, professor and chair of genetics at the Stanford School of Medicine said.
Dr. Snyder said that, once the algorithm is verified, the device could send physiological information that can alert users if their body is showing signs that it is fighting a viral infection. However, Dr. Snyder clarified that an ‘alert’ isn’t exactly a diagnosis because there are different things that can alter the signs that wearables monitor, such as increased heart rate when watching a horror movie. He added that their next step is to investigate whether the technology has the potential to differentiate the different types of viruses.