Inverse problems

Structural correlation method for practical estimation of patient specific parameters in heart rate regulation

Numerous mathematical models have been proposed for prediction of baroreflex regulation of heart rate. Most models have been designed to provide qualitative predictions of the phenomena, though some recent models have been developed to predict observed data. In this study we show how sensitivity and correlation analysis can be used for model reduction and for obtaining a set of identifiable parameters that can be estimated reliably given a model and an associated set of data. We show that the model developed by Bugenhagen et al.

Patient specific parameter estimation and heart rate regulation

Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities. Knowledge of variation in parameters within and between groups of subjects have potential to provide insight into biological function. Often it is not possible to estimate all parameters in a given model, in particular if the model is complex and the data is sparse.

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