A team of US researchers has found that smartphones are capable of detecting blood oxygen saturation levels as low as 70% – the lowest level a pulse oximeter should be able to measure.
The proof-of-principle research by University of Washington (UW) and University of California, San Diego The researchers involved participants placing their finger over the camera and flash of a smartphone that uses a deep learning algorithm to decipher blood oxygen levels.
When the team administered a controlled mixture of nitrogen and oxygen to six subjects to artificially lower their blood-oxygen levels, the smartphone correctly predicted if the subject had low blood-oxygen levels 80 percent of the time.
“Other smartphone apps that do this were developed by asking people to hold their breath. But people feel very uncomfortable and need to breathe after about a minute, and that’s before their blood oxygen levels have dropped far enough to represent the full range of clinically relevant data,” said co-lead author Jason Hoffman from the University of Washington.
“With our test, we can collect 15 minutes of data from each subject. Our data shows that smartphones could work well right in the critical threshold range,” Hoffman said in the study published in npj digital medicine.
also read
Another advantage of measuring blood oxygen levels on a smartphone is that almost everyone has one.
“In this way, you could perform multiple measurements with your own device, either for free or at low cost,” added co-author Dr. Matthew ThompsonProfessor of Family Medicine at Medical Faculty of the UW.
This would be very beneficial for telemedicine appointments to quickly determine if patients need to go to the ER or if they can continue resting at home and make an appointment with their GP later.
To collect data to train and test the algorithm, the researchers had each participant wear a standard pulse oximeter on one finger and then place another finger on the same hand over a smartphone’s camera and flash.
The researchers used the participants’ data to train a deep learning algorithm to determine blood oxygen levels. The rest of the data was used to validate the method and then test it to see how well it works in new subjects.
“The camera records how much the blood absorbs the light from the flash in each of the three color channels it measures: red, green, and blue,” said senior author Edward Wang, an assistant professor at UC San Diego.
The team hopes to continue this research by testing the algorithm on more people.
FacebookTwitterlinkedin
