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Cardiovascular oscillations: in search of a nonlinear parametric model

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>30/04/2003
<mark>Journal</mark>Proceedings of SPIE
Number of pages11
Pages (from-to)271-281
<mark>Original language</mark>English


We suggest a fresh approach to the modeling 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 modeling, able to contribute significantly towards the solution of a long standing challenge -- development of new diagnostic techniques based on noninvasive measurements.

Bibliographic note

Copyright 2003 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.