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A computationally efficient Hill curve adaptation strategy during continuous monitoring of dose–effect relation in anaesthesia

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Abstract

This paper discusses a possibility to simplify the number of parameters in the Hill curve by exploiting special mathematical functions. This simplification is relevant when adaptation is required for personalized model-based medicine during continuous monitoring of dose–response values. A mathematical framework of the involved physiology and modelling by means of distributed parameter progressions has been employed. Convergence to a unique dynamic response is achieved, allowing simplifying assumptions with guaranteed solution. Discussion on its use and comparison with other adaptation mechanism is provided.

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Acknowledgements

C. M. Ionescu is a postdoctoral fellow of the Flanders Research Centre (FWO), Grant No. 12B3415N. This research is financially supported by Flanders Research Centre, Grant No. G026514N.

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Authors and Affiliations

  1. Research Group on Dynamical Systems and Control, Faculty of Engineering and Architecture, Ghent University, Technologiepark 914, B9052, Zwijnaarde, Belgium

    Clara M. Ionescu

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  1. Clara M. Ionescu
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Correspondence to Clara M. Ionescu.

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Ionescu, C.M. A computationally efficient Hill curve adaptation strategy during continuous monitoring of dose–effect relation in anaesthesia. Nonlinear Dyn 92, 843–852 (2018). https://doi.org/10.1007/s11071-018-4095-3

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  • DOI: https://doi.org/10.1007/s11071-018-4095-3

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