A computationally efficient Hill curve adaptation strategy during continuous monitoring of dose–effect relation in anaesthesia
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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.
KeywordsHill curve Continuous fraction expansion Mathematical model Nonlinear dynamics Variability Dose–effect relation Patient specificity
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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