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Comparison of autoregressive and Fourier transform based techniques for estimating RR interval spectra

Lookup NU author(s): Dr Janet McComb, Emeritus Professor Alan MurrayORCiD


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Two fundamentally different approaches have been used to estimate spectra of RR interval series. The classical approach uses a Fourier transform (FT), and the model based approach uses an autoregressive (AR) model. The aim of this study was to compare estimates of both low frequency (LF) and high frequency (HF) heart rate variability (HRV) obtained using both FT and AR techniques. Five minute RR interval series were obtained from a group of normals (N=9) and a group of heart transplant patients with decreased HRV (N=9). For the normal group, mean LF power was 1164 ms(2) (SD 817 ms(2)) with the FT and 1358 ms(2) (SD 906 ms(2)) with the AR method. Mean HF power was 1010 ms(2) (SD 1321 ms(2)) with the FT and 442 ms(2) (SD 718 ms(2)) with the AR method. In the transplant group LF HRV was unmeasureable, and mean HF power was 2.39 ms(2) with the FT and 5.31 ms(2) with the AR method. Overall the two measures were well correlated (r=0.74). Both FT and AR spectra provide a comparable measure of LF and HF HRV.

Publication metadata

Author(s): Clayton RH, Lord SW, McComb JM, Murray A

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Computers in Cardiology 1997

Year of Conference: 1997

Pages: 379-382

Online publication date: 06/08/2002

ISSN: 0276-6547

Publisher: IEEE


DOI: 10.1109/CIC.1997.647912

Library holdings: Search Newcastle University Library for this item

ISBN: 0780344464