Literature DB >> 19670185

Dynamic modeling and identification of an axial flow ventricular assist device.

Francesco Moscato1, Guido A Danieli, Heinrich Schima.   

Abstract

An accurate characterization of the hemodynamic behavior of ventricular assist devices (VADs) is of paramount importance for proper modeling of the heart-pump interaction and the validation of control strategies. This paper describes an advanced test bench, which is able to generate complex hydraulic loads, and a procedure to characterize rotary blood pump performance in a pulsatile environment. Special focus was laid on model parameter identifiability in the frequency domain and the correlation between dynamic and steady-state models. Twelve combinations of different flow/head/speed signals, which covered the clinical VAD working conditions, were generated for the pump characterization. Root mean square error (RMSE) between predicted and measured flow was used to evaluate the VAD model. The found parameters were then validated with broadband random signals. In the experiments the optimization process always successfully converged. Even in the most demanding dynamic conditions the RMSE was 7.4 ml/sec and the absolute error never exceeded 24.9 ml/sec. Validity ranges for the identified VAD model were: flow 0-180 ml/sec; head 0-120 mmHg; speed 7.5-12.5 krpm. In conclusion, a universal test bench and a characterization procedure to describe the hydrodynamic properties of rotary blood pumps were established. For a particular pump, a reliable mathematical model was identified that correctly reproduced the relationship between instantaneous VAD flow, head and impeller speed.

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Year:  2009        PMID: 19670185     DOI: 10.1177/039139880903200604

Source DB:  PubMed          Journal:  Int J Artif Organs        ISSN: 0391-3988            Impact factor:   1.595


  7 in total

Review 1.  The use of computational fluid dynamics in the development of ventricular assist devices.

Authors:  Katharine H Fraser; M Ertan Taskin; Bartley P Griffith; Zhongjun J Wu
Journal:  Med Eng Phys       Date:  2010-11-13       Impact factor: 2.242

2.  Mechanical circulatory support device-heart hysteretic interaction can predict left ventricular end diastolic pressure.

Authors:  Brian Y Chang; Steven P Keller; Sonya S Bhavsar; Noam Josephy; Elazer R Edelman
Journal:  Sci Transl Med       Date:  2018-02-28       Impact factor: 17.956

Review 3.  Exercise physiology in left ventricular assist device patients: insights from hemodynamic simulations.

Authors:  Libera Fresiello; Christoph Gross; Steven Jacobs
Journal:  Ann Cardiothorac Surg       Date:  2021-05

4.  A Scalable Approach to Determine Intracardiac Pressure From Mechanical Circulatory Support Device Signals.

Authors:  Brian Y Chang; Christian Moyer; Ahmad El Katerji; Steven P Keller; Elazer R Edelman
Journal:  IEEE Trans Biomed Eng       Date:  2021-02-18       Impact factor: 4.538

5.  Hysteretic device characteristics indicate cardiac contractile state for guiding mechanical circulatory support device use.

Authors:  Brian Y Chang; Zhengyang Zhang; Steven P Keller; Elazer R Edelman; Kimberly Feng; Noam Josephy
Journal:  Intensive Care Med Exp       Date:  2021-12-20

6.  Estimation Methods for Viscosity, Flow Rate and Pressure from Pump-Motor Assembly Parameters.

Authors:  Martin Elenkov; Paul Ecker; Benjamin Lukitsch; Christoph Janeczek; Michael Harasek; Margit Gföhler
Journal:  Sensors (Basel)       Date:  2020-03-06       Impact factor: 3.576

7.  A Novel Control Method for Rotary Blood Pumps as Left Ventricular Assist Device Utilizing Aortic Valve State Detection.

Authors:  Dmitry Petukhov; Leonie Korn; Marian Walter; Dmitry Telyshev
Journal:  Biomed Res Int       Date:  2019-12-11       Impact factor: 3.411

  7 in total

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