Stochastic model of the human middle ear using a nonparametric probabilistic approach

Abstract

Several mathematical models of the human middle ear dynamics have been studied since the mid-twentieth century. Despite different methods applied, all of these models are based on deterministic approaches. Experimental data have shown that the middle ear behaves as an uncertain system due to the variability among individuals. In this context, stochastic models are useful because they can represent a population of middle ears with its intrinsic uncertainties. In this work, a nonparametric probabilistic approach is used to model the human middle ear dynamics. The lumped-element method is adopted to develop deterministic baseline models, and three different optimization processes are proposed and applied to the adjustment of the stochastic models. Results show that the stochastic models proposed can reproduce the experimental data in terms of mean and coefficient of variation. In addition, this study shows the importance of properly defining the acceptable range of each input parameter in order to obtain a reliable stochastic model.