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Data assimilation for identification of cardiovascular network characteristics
Author(s) -
Lal Rajnesh,
Mohammadi Bijan,
Nicoud Franck
Publication year - 2017
Publication title -
international journal for numerical methods in biomedical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.741
H-Index - 63
eISSN - 2040-7947
pISSN - 2040-7939
DOI - 10.1002/cnm.2824
Subject(s) - kalman filter , data assimilation , sensitivity (control systems) , algorithm , computer science , boundary (topology) , waveform , estimation theory , identification (biology) , inverse problem , extended kalman filter , mathematics , mathematical optimization , engineering , artificial intelligence , mathematical analysis , physics , telecommunications , radar , electronic engineering , meteorology , botany , biology
Summary 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.