Determination of Aortic Characteristic Impedance and Total Arterial Compliance From Regional Pulse Wave Velocities Using Machine Learning: An in-silico Study.

ABSTRACT: In-vivo assessment of aortic characteristic impedance (Z _ao ) and total arterial compliance (C _T ) has been hampered by the need for either invasive or inconvenient and expensive methods to access simultaneous recordings of aortic pressure and flow, wall thickness, and cross-sectional area. In contrast, regional pulse wave velocity (PWV) measurements are non-invasive and clinically available. In this study, we present a non-invasive method for estimating Z _ao and C _T using cuff pressure, carotid-femoral PWV (cfPWV), and carotid-radial PWV (crPWV). Regression analysis is employed for both Z _ao and C _T . The regressors are trained and tested using a pool of virtual subjects (

SUBMITTER: Bikia V 

PROVIDER: S-EPMC8155726 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature