Litcius/Paper detail

Estimating central blood pressure from aortic flow: development and assessment of algorithms

Jorge Mariscal Harana, Peter Charlton, Samuel Vennin, Jorge Aramburu, Mateusz C. Florkow, Arna van Engelen, Torben Schneider, Hubrecht de Bliek, Bram Ruijsink, Israel Valverde, Philipp Beerbaum, Heynric B. Grotenhuis, Marietta Charakida, Phil Chowienczyk, Spencer J. Sherwin, Jordi Alastruey

2020American Journal of Physiology-Heart and Circulatory Physiology39 citationsDOIOpen Access PDF

Abstract

First, our proposed methods for CV parameter estimation and a comprehensive set of methods from the literature were tested using in silico and clinical datasets. Second, optimized algorithms for estimating cBP from aortic flow were developed and tested for a wide range of cBP morphologies, including catheter cBP data. Third, a dataset of simulated cBP waves was created using a three-element Windkessel model. Fourth, the Windkessel model dataset and optimized algorithms are freely available.

Topics & Concepts

Aortic pressureIn silicoAlgorithmSet (abstract data type)Computer scienceRange (aeronautics)Data setFlow (mathematics)Data miningBlood pressureMathematicsMedicineInternal medicineArtificial intelligenceEngineeringBiologyGeometryProgramming languageAerospace engineeringGeneBiochemistryCardiovascular Health and Disease PreventionCardiovascular Function and Risk FactorsHemodynamic Monitoring and Therapy