Capillary Refill Time (CRT) is a traditional, semi-quantitative method used to estimate blood flow return to the skin after compression, with times over a few seconds deemed abnormal. Quantitative CRT (qCRT) aims to enhance traditional CRT by offering precise, mobile measurements crucial for telehealth. This study addresses important qCRT challenges, such as variation in skin phototype and the creation of a consistent, phototype-independent algorithm to reduce variability. We employed cross-polarized imaging and cocircular setups to reduce specular reflection, analyzing CRT decay across various color spaces in thirty-two volunteers of all Fitzpatrick phototypes. The sensing system was an RGB camera. We have showed that it is possible to produce qCRT results that are insensitive to phototype (melanin). However, the qCRT results, even for the same operational mechanics, show high sensitivity to the specific algorithm used for CRT determination. Since different algorithms exist to determine CRT, we discuss specific examples using two methods to analyze the CRT decay curve and three-color spaces (green channel, grayscale, and hemoglobin obtained by image processing).
Blood pressure (BP) is one of the most important indicators of physical and mental health. BP monitoring helps with controlling ailments such as heart disease and may help with stress assessment. Currently, BP measuring technologies use inflatable cuffs, which are inconvenient to use, being undesirable for continuous BP monitoring. Here we use photoplethysmographic (PPG) pulse wave contour to estimate BP using pulse decomposition analysis. As blood is ejected from the heart, the pulse moves both distally to the arms and down the aorta, partially reflecting at the renal and iliac arteries branches. These reflections move up the aorta and distally to the extremities, such that finger PPG signals are composed of three waves: the primary pulse and two delayed reflected waves. This model has been used by others, fitting Gaussian waves to the PPG signal. However, fitting stability and correlation with BP could be improved. In our proposed method, each PPG pulse is the sum of three hyperbolic secants (sech) waves, whose features are determined by PPG curve fitting. An increase in blood pressure makes pulse wave velocity increase, decreasing the intervals between waves. To verify the method, we have collected PPG signals and continuously measured BP from a volunteer. Multiple regression analysis between the PPG extracted features and continuous BP readings shows a very high correlation and high statistical significance. The decomposition in sech showed both higher stability and better correlation with BP than the Gaussian wave decompositions reported in the literature.
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