Towards Medical Cyber-Physical Systems: Modelica and FMI based Online Parameter Identification of the Cardiovascular System

Jonas Gesenhues
Institute of Automatic Control, RWTH Aachen University, Germany

Marc Hein
Department of Anesthesiology, RWTH Aachen University Hospital, Germany

Maike Ketelhut
Institute of Automatic Control, RWTH Aachen University, Germany

Thivaharan Albin
Institute of Automatic Control, RWTH Aachen University, Germany

Dirk Abel
Institute of Automatic Control, RWTH Aachen University, Germany

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp17132613

Ingår i: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017

Linköping Electronic Conference Proceedings 132:68, s. 613-621

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Publicerad: 2017-07-04

ISBN: 978-91-7685-575-1

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


This paper presents a concept for online parameter identification intended to be used within cardiovascular research labs and hospitals of the future featuring a data network of medical sensors. It is based on iterative nonlinear optimization using a moving horizon scheme and object-oriented Modelica models. Special FMUs have been developed to interface the optimization module and the sensor hardware. The concept is demonstrated on an exemplary application of identifying the parameters of a model for the systemic circulation. Unlike classical online parameter identification methods, this concept allows for quickly implementing changes of the underlying model.


Online Parameter Identification, Moving Horizon, FMI, ModeliChart, JModelica.org, CasADi, Cardiovascular, Medical


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