A Multi-Channel Ratio-of-Ratios Method for Noncontact Hand Video Based
SpO2 Monitoring Using Smartphone Cameras
Abstract
Blood oxygen saturation (SpO2) is an important indicator for pulmonary
and respiratory functionalities. Clinical findings on COVID-19 show that
many patients had dangerously low blood oxygen levels not long before
conditions worsened. It is therefore recommended, especially for the
vulnerable population, to regularly monitor the blood oxygen level for
precaution. Recent works have investigated how ubiquitous smartphone
cameras can be used to infer SpO2. Most of these works are
contact-based, requiring users to cover a phone’s camera and its nearby
light source with a finger to capture reemitted light from the
illuminated tissue. Contact-based methods may lead to skin irritation
and sanitary concerns, especially during a pandemic. In this paper, we
propose a noncontact method for SpO2 monitoring using hand videos
acquired by smartphones. Considering the optical broadband nature of the
red (R), green (G), and blue (B) color channels of the smartphone
cameras, we exploit all three channels of RGB sensing to distill the
SpO2 information beyond the traditional ratio-of-ratios (RoR) method
that uses only two wavelengths. To further facilitate an accurate SpO2
prediction, we design adaptive narrow bandpass filters based on
accurately estimated heart rate to obtain the most cardiac-related AC
component for each color channel. Experimental results show that our
proposed blood oxygen estimation method can reach a mean absolute error
of 1.26% when a pulse oximeter is used as a reference, outperforming
the traditional RoR method by 25%.