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

新型颜料感应脉搏血氧仪技术可减少血氧饱和度测量中的种族偏见

• 批准号: 10599746
• 负责人: Michael McGeehan
• 金额: $ 25.62万
• 依托单位: PENDERIA TECHNOLOGIES, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10599746
• 关键词: Adhesives; Admission activity; Adoption; Architecture; Biological; Blood; Blood gas; COVID-19; Caring; Classification; Clinical; Clip; Colorimetry; Compensation; Congresses; Custom; Darkness; Data; Development; Devices; Diagnosis; Disease; Electronics; Ensure; Equitable healthcare; Fingers; Forehead; Functional disorder; Funding; General Anesthesia; Goals; Growth; Health; Health Care Costs; Health Personnel; Healthcare; Hemoglobin; Hospitals; Hypoxemia; Individual; Intensive Care; Interview; Light; Machine Learning; Manufacturer; Marketing; Measurement; Measures; Medical; Medical Device; Medical Technology; Minority Groups; Mission; Modeling; Monitor; Nature; Nurses; Operative Surgical Procedures; Optics; Organ; Oxygen; Oxygen saturation measurement; Patient Care; Patient Monitoring; Patients; Performance; Persons; Phase; Photoplethysmography; Physicians; Physiologic pulse; Pigments; Procedures; Process; Pulse Oximetry; Radial; Research; Research Personnel; Safety; Sampling; Skin; Skin Pigmentation; Sleep Apnea Syndromes; Small Business Technology Transfer Research; Surveys; System; Technical Expertise; Techniques; Technology; Testing; Transducers; Translating; United States; Validation; Ventilator; Work; absorption; career networking; clinical investigation; clinical practice; cohort; commercialization; design; health care disparity; high reward; high risk; human subject; improved; innovation; innovative technologies; light scattering; machine learning algorithm; minority healthcare; mortality; new technology; novel; optical sensor; outcome disparities; people of color; prototype; racial bias; racial disparity; respiratory; sensor; sensor technology; signal processing; skin color; standard measure; success; technology development; wearable device; wireless electronic

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.

抽象的 可穿戴式脉搏血氧饱和度传感器是医疗保健领域最普遍使用的医疗技术之一。 临床医生依靠脉搏血氧计来监测疾病状态和医疗过程中患者的健康状况。 然而，大量研究表明，这项技术存在种族偏见，低氧血症是其三倍； 与浅色皮肤的患者相比，这种技术缺陷很可能在深色皮肤的患者中未被发现。 对美国有色人种的影响尤为严重，并加剧了少数族裔的医疗保健差距。 此后，FDA 发布了针对少数人群使用脉搏血氧测定法的安全警告。 水平可能表明患者患有严重的呼吸道疾病，医护人员依靠脉搏血氧计来检测 确定患者需要哪种类型的护理 假阴性低氧血症诊断可能会导致疼痛。 对患者护理的影响包括死亡率增加和器官功能障碍。 这些股权设备的有效使用凸显了对改善医疗保健的创新技术的迫切需求 并减少脉搏血氧测定中的种族偏见 尽管有充分记录的种族偏见，2022 年的脉搏调查。 血氧计技术发现没有制造商试图采用新技术来解决 该第一阶段项目的目标是开发新颖的非侵入式传感器技术。 测量血氧饱和度，考虑患者的皮肤色素并提供可靠准确的结果 我们提出的技术包含两种肤色的血氧饱和度测量。 传感模块：用于对患者肤色进行分类的新型皮肤色素比色传感器和光学传感器 我们将开发一种通过光电体积描记技术测量血氧饱和度的传感器。 机器学习算法来建模和补偿肤色对血氧饱和度的影响 这些技术开发和生物信号处理方面的创新将满足关键的要求。 需要一种能够为所有肤色的人提供准确血氧饱和度监测的医疗设备。