Friday, June 29, 2018
The researchers developed machine-learning AI algorithms which convert the information on the reflected waves into digital data for further analysis.
The algorithm can detect glucose changes based on more than 500 wave features or characteristics, which include the time taken to bounce back to the device.
The initial tests done with volunteers at the Research Institute for Aging in Waterloo showed 85 percent accurate results as opposed to conventional, traditional, invasive blood analysis. "The correlation was actually amazing. We have shown it is possible to use radar to look into the blood to detect changes," said Shaker.
