Estimating SpO2 with Deep Oxygen Desaturations from Facial Video Under Various Lighting Conditions: A Feasibility Study

This paper presents a feasibility study to collect data, process signals, and validate accuracy of peripheral oxygen saturation (SpO2) estimation from facial video in various lighting conditions. The remote photoplethysmogram (rPPG) signals were first extracted from the facial videos recorded using RGB camera without auto-tuning. These videos were collected from subjects breathing through mouth tube with their nose clipped. The air inhaled by the subjects were manually controlled to gradually induce hypoxemia and lower subjects’ SpO2 to as low as 81%. We applied the principle of pulse oximetry and extracted the ratio of ratios (RoR) for two color combinations: Red/Blue and Red/Green. Next, we assessed SpO2 estimation accuracy against a SpO2 multi-wavelength analyzer under four lighting conditions: warm color temperature and normal brightness, neutral color temperature and normal brightness, cool color temperature and normal brightness, neural color temperature and dim brightness. We have achieved an RMSE of 1.93% and a PCC of 0.97 under the warm color temperature and normal brightness lighting condition using leave-one-subject-out cross validation between two subjects. The results have shown that it is feasible to estimate SpO2 remotely and accurately using consumer level RGB camera with suitable camera configuration and lighting condition.