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An Ensemble Kalman filter-based data assimilation method effectively estimates cardiovascular network parameters, improving hemodynamic predictions.
A method to estimate the hemodynamics parameters of a network of vessels using an Ensemble Kalman filter is presented. The elastic moduli (Young's modulus) of blood vessels and the terminal boundary parameters are estimated as the solution of an inverse problem. Two synthetic test cases and a configuration where experimental data are available are presented. The sensitivity analysis confirms that the proposed method is quite robust even with a few numbers of observations. The simulations with the estimated parameters recovers target pressure or flow rate waveforms at given specific locations, improving the state-of-the-art predictions available in the literature. This shows the effectiveness and efficiency of both the parameter estimation algorithm and the blood flow model.
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Lal et al. (2016) studied this question. Ensemble Kalman filter for parameter estimation vs. State-of-the-art predictions was evaluated on Estimation of hemodynamics parameters (elastic moduli and terminal boundary parameters).
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