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.
|Title of host publication
|Computational & Mathematical Biomedical Engineering 2019 Proceedings
|Number of pages
|Published - 2019