Summary of article: AI$-$driven mobile health algorithm uses phone camera to detect blood vessel oxygen levels:

You may already use your smartphone for remote medical appointments. Why not use some of the onboard sensors to gather medical data? That's the idea behind AI$-$driven technology developed at Purdue University that could use a smartphone camera to detect and diagnose medical conditions like anemia faster and more accurately than highly specialized medical equipment being developed for the task.

"There are at least $15$ different sensors in your smartphone, and our goal is to take advantage of those sensors so people can access health care outside of a doctor's office," said lead researcher Young Kim, professor and associate head for research in Purdue's Weldon School of Biomedical Engineering. $"$To the best of our knowledge, we believe that we demonstrated the fastest hemodynamic imaging in existence, using a commercially available smartphone."

While a smartphone camera is convenient, it captures measurements of only red, green and blue wavelengths of light in each pixel, limiting its medical utility. Hyperspectral imaging can capture all wavelengths of visible light in each pixel and could be used to detect a variety of skin and retinal conditions and some cancers.

Researchers are exploring hyperspectral imaging health care applications, but most of the work is aimed at improving specialized equipment, which is relatively bulky, slow and expensive. By pairing deep learning and statistical techniques with their knowledge of light$-$tissue interactions, Purdue researchers are able to reconstruct the full spectrum of visible light in each pixel of an ordinary smartphone camera image. The patent$-$pending approach, from a lab with expertise in mobile health, could improve access to health care.

As reported in PNAS Nexus, the team tested its method against commercially available hyperspectral imaging equipment when gathering information about the movement of blood oxygen in volunteers' eyelids, in models meant to mimic human tissue, and in a chick embryo.

Results show the smartphone camera produced hyperspectral information more quickly, more cheaply and just as accurately as those captured using specialized equipment. The smartphone approach can produce images in a single millisecond that would take conventional hyperspectral imaging three minutes to capture.