Analysis and improvement of non-contact SpO2 extraction using an RGB webcam

Peripheral oxygen saturation (SpO2), a vital physiological sign employed in clinical care, is commonly obtained by using a contact pulse oximeter. With the rapid popularization of ordinary red-green-blue (RGB) webcams embedded in devices such as smartphones or laptops, there are broad application prospects for exploring techniques for non-contact SpO2 extraction using RGB webcams. However, many issues remain to be solved in the traditional webcam-based SpO2 extraction methods, such as the inherent low signal-to-noise ratio (SNR) of alternating current (AC) components of RGB signals and the potential defects in using RGB signals combination for SpO2 extraction. In this study, we conducted an in-depth examination of the existing research on webcam-based SpO2 extraction techniques, analyzed the practical problems in using them, and explored new ideas to solve the problems. Rather than roughly using the standard deviations (SD) of AC components for calculations, we performed blind source separation for AC components, and then used the energy coefficients retained in the mixed matrix to replace the variables required in the algorithm. Moreover, steady data was selected to compensate for the potential defects in using RGB signals combination. Through these efforts, the anti-noise capability of the algorithm was significantly enhanced, and the related defects were compensated for. The experimental results indicated that the proposed method produced reliable SpO2 estimation that could potentially-with further research-be used in real applications.