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Algorithm Uses Phone Camera to Detect Blood Oxygen Levels

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A smartphone camera paired with an AI-driven algorithm can capture blood oxygen data faster and more efficiently than highly specialized equipment.

The researchers used a computational approach that they described as “hyperspectral learning.”

Credit: Young Kim et al

Purdue University researchers have developed an algorithm to improve the speed and accuracy of medical diagnoses using smartphone sensors.

Although smartphone cameras capture only red, green, and blue wavelengths of light in each pixel, the researchers were able to reconstruct the full spectrum of visible light in each pixel of an image taken by a smartphone camera using deep learning, statistical techniques, and an understanding of light-tissue interactions.

The researchers found their technology produced information about blood oxygen levels in study participants' eyelids faster than commercially available hyperspectral imaging equipment, while being less expensive and just as accurate.

From Purdue University
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Abstracts Copyright © 2023 SmithBucklin, Washington, DC, USA


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