Time-variant spectral estimation of heart rate variability signal

A. Bianchi, L. Mainardi, M. G. Signorini, S. Cerutti, F. Lombardi, A. Montefusco, A. Malliani

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

Abstract

The authors describe some time-variant algorithms of autoregressive (AR) identification that result in obtaining a new set of AR parameters for each data sample. The performances of the algorithms were tested on simulated series to better understand their capability in tracking abrupt or constant-rate changes in the signal. A power spectrum density was obtained at each sample and a compressed spectrum array (CSA) graph is plotted. The algorithms were then applied in the study of the heart rate variability signal in dogs during coronary occlusion and in human subjects during transient ischemic episodes. Spectral parameters were obtained on a beat-to-beat basis, for a better comprehension of the dynamic role of the autonomic nervous system in this pathology.

Original languageEnglish
Title of host publicationComputers in Cardiology
PublisherPubl by IEEE
Pages265-268
Number of pages4
ISBN (Print)081862485X
Publication statusPublished - 1992
EventProceedings of the 18th Annual Conference on Computers in Cardiology - Venice, Italy
Duration: Sep 23 1991Sep 26 1991

Other

OtherProceedings of the 18th Annual Conference on Computers in Cardiology
CityVenice, Italy
Period9/23/919/26/91

ASJC Scopus subject areas

  • Software
  • Cardiology and Cardiovascular Medicine

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