Real-Time SpO2 Estimation from Chest Reflectance Photoplethysmography: Algorithm Development and Clinical Validation Against Arterial SaO2

Abstract

Peripheral oxygen saturation (SpO2) estimation using photoplethysmography (PPG) is typically based on the pulsatile components of red and infrared (IR) PPG signals acquired from peripheral sites, such as the finger or earlobe. Although these sites provide strong PPG signals, they are less suitable for integrated monitoring with electrocardiography (ECG), including arrhythmia detection. Simultaneous acquisition of PPG and ECG from a chest-worn device may therefore enable continuous and integrated physiological monitoring. However, chest PPG is characterized by lower perfusion and greater susceptibility to respiratory and motion artifacts, making reliable extraction of pulsatile red and IR components challenging. In this study, we developed and clinically evaluated a real-time SpO2 estimation algorithm based on chest reflectance PPG. Green PPG, which provides a relatively distinct pulsatile waveform under low-perfusion conditions, was used for beat detection. A heart-rate-adaptive analysis window, normalized cross-correlation-based signal quality assessment, and least-squares estimation of the AC amplitude ratio were combined to calculate the red-to-IR ratio of ratios, from which SpO2 was estimated using a calibration equation. Algorithm performance was evaluated against reference arterial oxygen saturation (SaO2) measured using a blood gas analyzer. The proposed method achieved an accuracy root mean square of 2.91% relative to the reference SaO2. These results support the technical feasibility of chest reflectance PPG-based SpO2 estimation and its accuracy under controlled desaturation conditions.