Multivariate ARMA spectral decomposition in the assessment of cardiovascular variabilities

G. Baselli, A. Porta, G. Ferrari, S. Cerutti, O. Rimoldi, M. Pagani, A. Malliani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multi-variate spectral analysis is able to describe the interactions between heart rate and arterial pressure variabilities; therefore, it provides a spectral decomposition based on which signal is driven more directly or on which closed-loop resonance is involved. So, it provides further insight in the genesis of rhythms, beyond the classical definition of low frequency (LF) and high frequency (HF) components related to mono-variate spectral analysis. The method of spectral decomposition is presented both for the identification of bi-variate autoregressive models, which is a general signal processing tool, and for a dynamic adjustment model specific for cardiovascular variabilities. Preliminary results on conscious dogs under various sympathetic stimuli enhancing LF rhythms confirm the existence of different mechanisms which contribute to these waves.

Original languageEnglish
Title of host publicationComputers in Cardiology
PublisherPubl by IEEE
Pages731-734
Number of pages4
ISBN (Print)0818654708
Publication statusPublished - 1993
EventProceedings of the 1993 Conference on Computers in Cardiology - London, UK
Duration: Sep 5 1993Sep 8 1993

Other

OtherProceedings of the 1993 Conference on Computers in Cardiology
CityLondon, UK
Period9/5/939/8/93

ASJC Scopus subject areas

  • Software
  • Cardiology and Cardiovascular Medicine

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