Smartphone camera oximetry in an induced hypoxemia study.
cross_sectional · Level IV
Where this comes from
- Record sourced from PubMed, PMID 36123367.
- Also identified by DOI 10.1038/s41746-022-00665-y and PMC identifier 9483471.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Hypoxemia, a medical condition that occurs when the blood is not carrying enough oxygen to adequately supply the tissues, is a leading indicator for dangerous complications of respiratory diseases like asthma, COPD, and COVID-19. While purpose-built pulse oximeters can provide accurate blood-oxygen saturation (SpO<sub>2</sub>) readings that allow for diagnosis of hypoxemia, enabling this capability in unmodified smartphone cameras via a software update could give more people access to important information about their health. Towards this goal, we performed the first clinical development validation on a smartphone camera-based SpO<sub>2</sub> sensing system using a varied fraction of inspired oxygen (FiO<sub>2</sub>) protocol, creating a clinically relevant validation dataset for solely smartphone-based contact PPG methods on a wider range of SpO<sub>2</sub> values (70-100%) than prior studies (85-100%). We built a deep learning model using this data to demonstrate an overall MAE = 5.00% SpO<sub>2</sub> while identifying positive cases of low SpO<sub>2</sub> < 90% with 81% sensitivity and 79% specificity. We also provide the data in open-source format, so that others may build on this work.