An assessment of algorithms to estimate central blood pressure from non-invasive measurements

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

Central blood pressure (cBP) is a better cardiovascular risk indicator than brachial pressure. We propose a non-invasive approach to estimate cBP combining medical image data and reduced-order models of arterial haemodynamics. This approach (i) estimates cardiovascular parameters from noninvasive data; and (ii) uses these parameters as inputs to one of three cBP estimation models. We assessed the performance of each model by comparing estimated and reference values of pulse pressure for an in silico dataset.
Original languageEnglish
Title of host publicationComputational & Mathematical Biomedical Engineering 2019 Proceedings
Pages603-606
Number of pages4
Volume2
Publication statusPublished - 2019

Publication series

NameCMBE Proceedings
ISSN (Print)2227-9385
ISSN (Electronic)2227-3085

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