Data Driven Lossy Tube Load Modeling of Arterial Tree: In Human Study

Abstract

In this paper, we present and validate a datadriven method to lossy tubeload modeling of arterial tree in humans. In the proposed method, the lossy tubeload model is fitted to central aortic and peripheral blood pressure (BP) waves in the time domain. For this purpose, we employ a timedomain lossy tubeload model in which the wave propagation constant is formulated to two terms: one responsible for the alteration of wave amplitude and the other for the transport delay. Using the experimental BP data collected from 17 cardiac surgery patients, we showed that the timedomain lossy tubeload model is able to accurately represent the relation between central aortic versus upperlimb and lowerlimb BP waves. In addition, the comparison of lossy versus lossless tubeload models revealed that (1) the former outperformed the latter in general with the rootmeansquared errors (RMSE) of 3.1 mm Hg versus 3.5 mm Hg, respectively (pvalue < 0.05), and (2) the efficacy of the former over the latter was more clearly observed in case the normalized difference in the mean central aortic versus peripheral BP was large; when the difference was >5% of the underlying mean BP, lossy and lossless models showed the RMSE of 2.7 mm Hg and 3.7 mm Hg, respectively (pvalue < 0.05).