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
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http://dx.doi.org/10.3384/ecp17132613Published in: Proceedings of the 12th International Modelica Conference, Prague, Czech Republic, May 15-17, 2017
Linköping Electronic Conference Proceedings 132:68, p. 613-621
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
J. Åkesson, K.-E. Årzén, M. Gäfvert, T. Bergdahl, and H. Tummescheit. Modeling and optimization with Optimica and JModelica.org—languages and tools for solving large-scale dynamic optimization problems. Computers & Chemical Engineering, 34(11):1737–1749, November 2010. doi: https://doi.org/10.1016/j.compchemeng.2009.11.011.
Joel Andersson, Johan Åkessona, Francesco Casellad, and Moritz Diehl. Integration of CasADi and JModelica.org. In Proceedings from the 8th International Modelica Conference, Technical Univeristy, Dresden, Germany, pages 218–231. Linkoping University Electronic Press, June 2011. doi: https://doi.org/10.3384/ecp11063218.
A. Brunberg, J. Maschuw, R. Autschbach, and D. Abel. Objectoriented model library of the cardiovascular system including physiological control loops. In IFMBE Proceedings, pages 166–169. Springer Nature, 2009. doi: https://doi.org/10.1007/978-3-642-03895-2_48.
John W. Clark, Robert Y. S. Ling, R. Srinivasan, J. S. Cole, and Roderick C. Pruett. A two-stage identification scheme for the determination of the parameters of a model of left heart and systemic circulation. IEEE Transactions on Biomedical Engineering, BME-27(1):20–29, January 1980. doi: https://doi.org/10.1109/tbme.1980.326687.
European Commission. Joint report on health care and long-term care systems & fiscal sustainability. European Economy Institutional Papers, (037), October 2016. doi: https://doi.org/10.2765/680422.
Jonas Gesenhues, Marc Hein, Moriz Habigt, Mare Mechelinck, Thivaharan Albin, and Dirk Abel. Nonlinear object-oriented modeling based optimal control of the heart: Performing precise preload manipulation maneuvers using a ventricular assist device. In 2016 European Control Conference (ECC). Institute of Electrical and Electronics Engineers (IEEE), June 2016. doi: https://doi.org/10.1109/ecc.2016.7810603.
Jonas Gesenhues, Marc Hein, Maike Ketelhut, Moriz Habigt, Daniel Rüschen, Mare Mechelinck, Thivaharan Albin, Steffen Leonhardt, Thomas Schmitz-Rode, Rolf Rossaint, Rüdiger Autschbach, and Dirk Abel. Benefits of object-oriented models & ModeliChart: Modern tools and methods for the interdisciplinary research on smart biomedical technology. Biomedical Engineering / Biomedizinische Technik, 2017. doi: https://doi.org/10.1515/bmt-2016-0074.
Moriz Habigt, Maike Ketelhut, Jonas Gesenhues, Frank Schrödel, Marc Hein, Mare Mechelinck, Thomas Schmitz-Rode, Dirk Abel, and Rolf Rossaint. Comparison of novel physiological load-adaptive control strategies for ventricular assist devices. Biomedical Engineering / Biomedizinische Technik, 2016. doi: https://doi.org/10.1515/bmt-2016-0073.
C.E. Hann, J.G. Chase, and G.M. Shaw. Integral-based identification of patient specific parameters for a minimal cardiac model. Computer Methods and Programs in Biomedicine, 81(2):181–192, February 2006. doi: https://doi.org/10.1016/j.cmpb.2005.11.004.
Maike Ketelhut, Frank Schrödel, Sebastian Stemmler, Jesse Roseveare, Marc Hein, Jonas Gesenhues, Thivarian Albin, and Dirk Abel. Iterative learning control of a left ventricular assist device. In 19th IFAC World Congress, Accepted for publication. Toulouse, France, 2017.
Ryo Kosaka, Yoshiyuki Sankai, Tomoaki Jikuya, Takashi Yamane, and Tatsuo Tsutsui. Online parameter identification of second-order systemic circulation model using the delta operator. Artificial Organs, 26(11):967–970, November 2002. doi: https://doi.org/10.1046/j.1525-1594.2002.07112.x.
Marek Mateják, Tomáš Kulhánek, Jan Šilar, Pavol Privitzer, Filip Ježek, and Ji?rí Kofránek. Physiolibrary – modelica library for physiology. In Proceedings of the 10th International Modelica Conference, March 10-12, 2014, Lund, Sweden. Linkoping University Electronic Press, March 2014. doi: https://doi.org/10.3384/ecp14096499.
Berno J.E. Misgeld, Daniel Rüschen, Sebastian Schwandtner, Stefanie Heinke, Marian Walter, and Steffen Leonhardt. Robust decentralised control of a hydrodynamic human circulatory system simulator. Biomedical Signal Processing and Control, 20:35–44, July 2015. doi: https://doi.org/10.1016/j.bspc.2015.04.004.
Ajay Moza, Jonas Gesenhues, Dirk Abel, Rolf Rossaint, Thomas Schmitz-Rode, and Andreas Goetzenich. Patient specific parameter estimation for cardiovascular system models based on clinical measurements. Biomedical Engineering / Biomedizinische Technik, 2017. doi: https://doi.org/10.1515/bmt-2016-0078.
M Nichols, N Townsend, R Luengo-Fernandez, J Leal, A Gray, P Scarborough, and M Rayner. European cardiovascular disease statistics 2012. european heart network, brussels, European society of cardiology, sophia antipolis. 2012. Cerebrovasc. Dis, 25:457–507, 2012.
Daniel Rüschen, Miriam Rimke, Jonas Gesenhues, Steffen Leonhardt, and Marian Walter. Online cardiac output estimation during transvalvular left ventricular assistance. Computer Methods and Programs in Biomedicine, August 2016. doi: https://doi.org/10.1016/j.cmpb.2016.08.020.
Andreas Wächter and Lorenz T. Biegler. On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming. Mathematical Programming, 106 (1):25–57, April 2005. doi: https://doi.org/10.1007/s10107-004-0559-y.
Nico Westerhof, Jan-Willem Lankhaar, and BerendE. Westerhof. The arterial windkessel. Medical & Biological Engineering & Computing, 47(2):131–141, 2009. ISSN 0140-0118. doi: https://doi.org/10.1007/s11517-008-0359-2.
Yih-Choung Yu, J.R. Boston, M.A. Simaan, and J.F. Antaki. Estimation of systemic vascular bed parameters for artificial heart control. IEEE Transactions on Automatic Control, 43 (6):765–778, June 1998. doi: https://doi.org/10.1109/9.679017.
