Development and Validation of an Algorithm for Calibrating Photoplethysmography Integrated Device

In the rapidly evolving landscape of technology, wearable devices wearable devices such as smartwatches and ear-cuffs have evolved into indispensable tools for maintaining health and well-being. Effortlessly integrating into daily routines, these versatile gadgets offer a plethora of functionalities ranging from enhancing workplace safety to tracking fitness goals. The recent surge in telemedicine has further propelled their adoption in clinical environments, where they play a crucial role in real-time health monitoring. While initially designed for cardiovascular applications, there is a growing interest in utilizing wearable devices, especially photoplethysmography, for assessing respiratory health. Photoplethysmography, commonly found in medical devices like pulse oximeters and blood pressure monitors, employs minimal optoelectronic components to measure fluctuations in light intensity associated with tissue perfusion changes. Through the emission of light into the skin and subsequent measurement of its absorption, reflection, or transmission, photoplethysmography devices offer valuable analysis, delineating distinct systolic and diastolic phases, thus aiding in assessing cardiovascular and respiratory functions as SpO2. This paper first considers the proposed algorithm using synthesized PPG signals. Then, we evaluate the experimental calibration curve correlating the average PPG ratio with SpO2 levels by collecting signals from a cohort of twenty healthy subjects with an average age of 23 years. Calibration is conducted utilizing SpO2 values obtained from a certified medical device compliant with the ISO/CD 80601-2-61 standard, showing a linear calibration equation with an R2 = 0.997, an RMSE = 0.11 and a maximum uncertainty of 3.7%.