Cardiovascular Oscillations: In Search of a Nonlinear Parametric Model

摘要

We suggest a fresh approach to the modelling of the human cardiovascular system. Taking advantage of a new Bayesian inference technique, able to deal with stochastic nonlinear systems, we show that one can estimate parameters for models of the cardiovascular system directly from measured time series. We present preliminary results of inference of parameters of a model of coupled oscillators from measured cardiovascular data addressing cardiorespiratory interaction. We argue that the inference technique offers a very promising tool for the modelling, able to contribute significantly towards the solution of a long standing challenge -development of new diagnostic techniques based on noninvasive measurements.