A smartphone application that tracks a person’s heart rate may be able to detect diabetes using a photoplethysmography signal, which is easily measured using a smartphone’s light and camera, according to a study presented at the American College of Cardiology Scientific Session.

The application developers demonstrated that by using deep learning and a smartphone camera alone, they could also detect vascular changes associated with diabetes and with reasonable discrimination.

While analyzing the heart rate data as collected using smartphone apps in the Health eHeart study, researchers noticed that patients with diabetes had, on average, a higher ‘free-living’ heart rate than patients without diabetes when adjusted for multiple factors.

Variations in blood volume that occur with every heart beat can be captured by shining a smartphone flashlight on a fingertip. With every heart contraction, BP increases in the vessels, causing them to expand, which then increases the amount of light reflected by the skin to the optical sensor of the phone’s camera. This input can then be converted to a waveform representing the volumetric change of the blood volume in a vessel.