On the use of the Akaike information criterion in AR spectral analysis of cardiovascular variability signals: a case report study

G. D. Pinna, R. Maestri, A. Di Cesare

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

Abstract

In order to better understand the relationship between model order selection by the Akaike Information Criterion (AIC) and AR spectral fidelity in the analysis of cardiovascular variability signals, we selected a set of signals (pulse interval, invasive and non invasive systolic and diastolic arterial pressure) characterized by having major oscillations easily recognizable by eye and clearly detected by the Blackman-Tukey spectral estimator. After model order estimation by the AIC and AR spectral estimation, we checked if main spectral features were actually reproduced. The sample records were chosen 3 min long. In most cases the AR estimator failed in resolving spectral components in the low frequency region ( 18), all missed peaks were always resolved. Our results suggest that AR spectral estimation based on automatic selection of model order by the AIC may lead to oversmoothed spectra, masking some oscillatory characteristics of cardiovascular variability signals.

Original languageEnglish
Title of host publicationComputers in Cardiology
PublisherPubl by IEEE
Pages471-474
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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