Factitious Hemoperfusion Based ROI Optimization in PPGi Analysis and its Application for Blood Pressure Determination

Abstract

Photoplethysmography Imaging (PPGi) is an emerging technology to monitor physiological parameters. However, the signal-to-noise ratio in PPGi usually is low due to inappropriate selection of Region of Interest (ROI). Herein, to enhance the signal-to-noise ratio, an optimization approach for ROI selection is proposed based on factitious hemoperfusion. Factitious hemoperfusion is able to amplify instantaneous blood volume and augment the volume of the blood vessel, and such an amplification will facilitate the identification of dense vessel regions as the optimized ROIs for PPGi. Furthermore, a self-adaptive PPGi denoising method is created to purify PPGi data, and an approach calculating Blood Pressure (BP) from PPGi signals is proposed and developed. Through comparing the calculated BP values to the ones measured using a commercial sphygmomanometer, it is found that the BP values resulted from the optimized ROIs are closer to the measured ones (with an error rate less than 5%).