Synthetic pulse wave dataset for analysis of vascular ageing in elderly patients

This paper presents a methodology to generate synthetic pulse wave database. Each virtual subject is generated with the help of one-dimensional hemodynamics model of systemic circulation with lumped model of the left heart. This paper describes and compares two parameter optimization methods: unscen...

Full description

Saved in:
Bibliographic Details
Published inMathematical modelling of natural phenomena Vol. 19; p. 20
Main Authors Rogov, Artem, Gamilov, Timur, Bragina, Anna, Abdullaev, Magomed, Druzhinina, Natalia, Rodionova, Yuliya, Shikhmagomedov, Rustam, Tyulin, Maksim, Podzolkov, Valeriy
Format Journal Article
LanguageEnglish
Published 2024
Online AccessGet full text

Cover

More Information
Summary:This paper presents a methodology to generate synthetic pulse wave database. Each virtual subject is generated with the help of one-dimensional hemodynamics model of systemic circulation with lumped model of the left heart. This paper describes and compares two parameter optimization methods: unscented Kalman filter and Bayesian optimization. As a case study, an experiment is conducted to predict cardio-ankle vascular index (CAVI) values for real individuals with a machine learning algorithm trained on a synthetic population. The average error of 6.5% is achieved
ISSN:0973-5348
1760-6101
DOI:10.1051/mmnp/2024017