Parameter estimation by descent and genetic algorithm methods of an in-vitro stenosis bypass model

The development of improved hemodynamic impedance models can greatly aid the understanding of arterial disease progression and its remediation. This paper leverages the recent progress in advanced manufacturing techniques to engage in in-vitro experimentation with physiologically relevant geometries and flows that correspond to arterial stenosis. The measurements of pressures and flow obtained by these experiments were then used to estimate flow-to-pressure transfer functions, aimed at determining a lumped-parameter impedance model of the physical system, by applying conventional descent as well as recently developed Genetic Algorithm methods. The resulting transfer functions can now be utilized for further studies with regard to the hemodynamics relevant to arterial stenosis.