Neuromuscular blockade model identification based on the Hill function inversion

The purpose of the work described in this paper is to assess the identification of a neuromuscular blockade model using the data obtained from the response of the first bolus during a general anesthesia. The aim is to use the identified model to help on the selection of a controller to be used during neuromuscular blockade control. The identification methodology explores the structure of the nonlinear Hill function that characterizes the pharmacodynamics and uses it to transform data that may be fitted into a dynamic linear model corresponding to the pharmacokinetics. The dynamics of the pharmacokinetic model is identified using Least Squares estimation. Computer simulations are used to evaluate the methodology. The simulation results show that the methodology provides good results but some a priori knowledge must be used, an estimate of the Hill parameter (γ) and the pharmacokinetics transfer function degrees.