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Inference of a nonlinear stochastic model of the cardiorespiratory interaction.

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>8/03/2005
<mark>Journal</mark>Physical Review Letters
Issue number9
Volume94
Pages (from-to)098101
<mark>State</mark>Published
<mark>Original language</mark>English

Abstract

We reconstruct a nonlinear stochastic model of the cardiorespiratory interaction in terms of a set of polynomial basis functions representing the nonlinear force governing system oscillations. The strength and direction of coupling and noise intensity are simultaneously inferred from a univariate blood pressure signal. Our new inference technique does not require extensive global optimization, and it is applicable to a wide range of complex dynamical systems subject to noise.

Bibliographic note

First use of Bayesian inference to build a nonlinear stochastic model of the cardio-respiratory interaction in terms of polynomial basis functions, directly from a univariate blood pressure signal. The technique is widely applicable in dynamical modelling. RAE_import_type : Journal article RAE_uoa_type : Physics