Technology could enable patients to monitor their own oxygen levels and transmit that data to healthcare providers, including clinical laboratories
Clinical laboratories may soon have a new data point to add to their laboratory information system (LIS) for doctors to review. Researchers have determined that smartphones can read blood-oxygen levels as accurately as purpose-built pulse oximeters.
Conducted by researchers at the University of Washington (UW) and University of California San Diego (UC San Diego), the proof-of-concept study found that an unmodified smartphone camera and flash along with an app is “capable of detecting blood oxygen saturation levels down to 70%. This is the lowest value that pulse oximeters should be able to measure, as recommended by the US Food and Drug Administration,” according to Digital Health News.
This could mean that patients at risk of hypoxemia, or who are suffering a respiratory illness such as COVID-19, could eventually add accurate blood-oxygen saturation (SpO2) readings to their lab test results at any time and from any location.
The researchers published their findings in the journal NPJ Digital Medicine titled, “Smartphone Camera Oximetry in an Induced Hypoxemia Study.”
“In an ideal world, this information could be seamlessly transmitted to a doctor’s office. This would be really beneficial for telemedicine appointments or for triage nurses to be able to quickly determine whether patients need to go to the emergency department or if they can continue to rest at home and make an appointment with their primary care provider later,” Matthew Thompson, DPhil, Professor of Global Health and Family Medicine at University of Washington, told Digital Health News. Clinical laboratories may soon have a new data point for their laboratory information systems. (Photo copyright. University of Washington.)
UW/UC San Diego Study Details
The researchers studied three men and three women, ages 20-34. All were Caucasian except for one African American, Digital Health News reported. To conduct the study, a standard pulse oximeter was placed on a finger and, on the same hand, another of the participant’s fingers was placed over a smartphone camera.
“We performed the first clinical development validation on a smartphone camera-based SpO2 sensing system using a varied fraction of inspired oxygen (FiO2) protocol, creating a clinically relevant validation dataset for solely smartphone-based contact PPG [photoplethysmography] methods on a wider range of SpO2 values (70–100%) than prior studies (85–100%). We built a deep learning model using this data to demonstrate an overall MAE [Mean Absolute Error] = 5.00% SpO2 while identifying positive cases of low SpO2 < 90% with 81% sensitivity and 79% specificity,” the researchers wrote in NPJ Digital Medicine.
When the smartphone camera’s flash passes light through the finger, “a deep-learning algorithm deciphers the blood oxygen levels.” Participants were also breathing in “a controlled mixture of oxygen and nitrogen to slowly reduce oxygen levels,” Digital Health News reported.
“The camera is recording a video: Every time your heart beats, fresh blood flows through the part illuminated by the flash,” Edward Wang, PhD, Assistant Professor of Electrical and Computer Engineering at UC San Diego and senior author of the project, told Digital Health News. Wang started this project as a UW doctoral student studying electrical and computer engineering and now directs the UC San Diego DigiHealth Lab.
“The camera records how much that blood absorbs the light from the flash in each of the three color channels it measures: red, green, and blue. Then we can feed those intensity measurements into our deep-learning model,” he added.
The deep learning algorithm “pulled out the blood oxygen levels. The remainder of the data was used to validate the method and then test it to see how well it performed on new subjects,” Digital Health News reported.
“Smartphone light can get scattered by all these other components in your finger, which means there’s a lot of noise in the data that we’re looking at,” Varun Viswanath, co-lead author in the study, told Digital Health News. Viswanath is a UW alumnus who is now a doctoral student being advised by Wang at UC San Diego.
“Deep learning is a really helpful technique here because it can see these really complex and nuanced features and helps you find patterns that you wouldn’t otherwise be able to see,” he added.
Each round of testing took approximately 15 minutes. In total the researchers gathered more than 10,000 blood oxygen readings. Levels ranged from 61% to 100%.
“The smartphone correctly predicted whether the subject had low blood oxygen levels 80% of the time,” Digital Health News reported.
Smartphones Accurately Collecting Data
The UW/UC San Diego study is the first to show such precise results using a smartphone.
“Other smartphone apps that do this were developed by asking people to hold their breath. But people get very uncomfortable and have to breathe after a minute or so, and that’s before their blood-oxygen levels have gone down far enough to represent the full range of clinically relevant data,” said Jason Hoffman, a PhD student researcher at UW’s UbiComp Lab and co-lead author of the study.
The ability to track a full 15 minutes of data is a prime example of improvement. “Our data shows that smartphones could work well right in the critical threshold range,” Hoffman added.
“Smartphone-based SpO2 monitors, especially those that rely only on built-in hardware with no modifications, present an opportunity to detect and monitor respiratory conditions in contexts where pulse oximeters are less available,” the researchers wrote.
“This way you could have multiple measurements with your own device at either no cost or low cost,” Matthew Thompson, DPhil, Professor of Global Health and Family Medicine at University of Washington, told Digital Health News. Thompson is a professor of both family medicine and global health and an adjunct professor of pediatrics at the UW School of Medicine.
What Comes Next
The UW/UC San Diego research team plans to continue its research and gather more diversity among subjects.
“It’s so important to do a study like this,” Wang said. “Traditional medical devices go through rigorous testing. But computer science research is still just starting to dig its teeth into using machine learning for biomedical device development and we’re all still learning. By forcing ourselves to be rigorous, we’re forcing ourselves to learn how to do things right.”
Though no current clinical laboratory application is pending, smartphone use to capture biometrics for testing is increasing. Soon, labs may need a way to input all that data into their laboratory information systems. It’s something to consider.
—Kristin Althea O’Connor
Related Information:
A Smartphone’s Camera and Flash could Help People Measure Blood Oxygen Levels at Home
Smartphones Can Measure Blood Oxygen Levels at Home
Smartphone’s Camera, Flash, Can Measure Blood Oxygen Up to 70% at Home