Several previous studies have proven that smartphones can be used to measure blood oxygen (SpO2) levels in users. Moreover, in 2020, several apps claimed to serve the same purpose and were even available on the Play Store. These apps were later removed due to concerns about their accuracy. Now, a new study conducted by the researchers of the University of Washington and the University of California San Diego has authenticated these measurements across a wide range of clinically relevant SpO2 levels.
During this study, researchers were able to measure accurate levels of blood oxygen saturation down to 70% using a smartphone’s camera and flash module. This proves that users will soon be able to correctly measure their blood oxygen saturation levels with smartphones that are more easily accessible.
How was this study conducted
Researchers asked the study participants to place their fingers over the camera and flash setup of a Google Nexus 6P smartphone. The device’s flash illuminated with every heartbeat when fresh blood flowed through that part of the finger. Also, the handset’s camera recorded a video to measure the amount of light from the glass that was absorbed by the blood across three channels — red, green and blue.
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Before validating the model on other participants, data from four earlier participants were used to train a deep learning (DL) algorithm that helped in measuring the blood oxygen saturation. This technology was continued to accurately predict the SpO2 levels of the six subjects whose blood oxygen levels were brought down by the research team using a controlled mixture of nitrogen and oxygen.
How can this technology be used in the upcoming days
These researchers have already applied for a patent for this technology. Although the technology has been tested only with a single smartphone model, the researchers are positive that it can be used across a wider variety of devices in the upcoming days.
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Also, the technology has to be tested on multiple smartphones as the researchers altered some configurations on the smartphone to use it to take the measurements. However, the team hopes to continue with the research by trying the new algorithm on several other test subjects.
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