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Updated: Jun 24, 2026

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
Published on: February 13, 2021
Modelling and disentangling physiological mechanisms: linear and nonlinear identification techniques for analysis of
Jerry Batzel1, Giuseppe Baselli, Ramakrishna Mukkamala
1Institute for Mathematics and Scientific Computing, University of Graz, 8010 Graz, Austria. jerry.batzel@uni-graz.at
Abstract:
Cardiovascular (CV) regulation is the result of a number of very complex control interactions. As computational power increases and new methods for collecting experimental data emerge, the potential for exploring these interactions through modelling increases as does the potential for clinical application of such models. Understanding these interactions requires the application of a diverse set of modelling techniques. Several recent mathematical modelling techniques will be described in this review paper. Starting from Granger's causality, the problem of closed-loop identification is recalled. The main aspects of linear identification and of grey-box modelling tailored to CV regulation analysis are summarized as well as basic concepts and trends for nonlinear extensions. Sensitivity analysis is presented and discussed as a potent tool for model validation and refinement. The integration of methods and models is fostered for a further physiological comprehension and for the development of more potent and robust diagnostic tools.
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