Novel Pigment Sensing Pulse Oximeter Technology for Mitigating Racial Bias in Oxygen Saturation Measurements

Penderia Technologies, Inc., Eugene OR

Investigators

Abstract

Abstract Wearable pulse oximetry sensors are among the most ubiquitous medical technologies used in healthcare. Clinicians rely on pulse oximeters to monitor patient health during disease states and medical procedures. However, numerous studies have shown this technology to be racially biased; hypoxemia is three times more likely to go undetected in patients with dark skin compared to those with light skin. This technological deficit disproportionately impacts people of color in the United States and contributes to minority healthcare disparities. The FDA has since issued a safety warning about using pulse oximetry for minority populations. Low blood oxygen levels can signify serious respiratory illness in a patient and healthcare workers rely on pulse oximeters to determine what type of care a patient needs. False negative hypoxemia diagnosis can have detrimental consequences for patient care including increased rates of mortality and organ dysfunction. The widespread and impactful use of these devices highlights a critical need for innovative technology that improves healthcare equity and mitigates racial bias in pulse oximetry. Despite well-documented racial biases, a 2022 survey of pulse oximeter technology found no manufacturers attempting to incorporate novel technology that accounts for differences in skin tone. The goal of this Phase I project is to develop novel sensor technology for non-invasively measuring blood oxygen saturation that accounts for the patient’s skin pigment and delivers reliably accurate oxygen saturation measurements for persons of all skin colors. Our proposed technology incorporates two sensing modules: a novel skin pigment colorimetry sensor for classifying patient skin tone and an optical transducer for measuring blood oxygen saturation via the photoplethysmography technique. We will develop a machine learning algorithm to model and compensate for the effects of skin tone on blood oxygen saturation measurements. These innovations in technology development and biological signal processing will meet a critical need for a medical device that provides accurate blood oxygen saturation monitoring for persons of all skin colors.