A methodological comparison of the Porges algorithm, fast Fourier transform, and autoregressive spectral analysis for the estimation of heart rate variability in 5‐month‐old infants. (24th February 2014)

• Record Type: Journal Article
• Authors: Poliakova, Natalia; Dionne, Ginette; Dubreuil, Etienne; Ditto, Blaine; Pihl, Robert O.; Pérusse, Daniel; Tremblay, Richard E.; Boivin, Michel
• Is Part Of: Psychophysiology. Volume 51:Number 6(2014:Jun.)
• Page Start: 579
• Page End: 583
• Publication Date: 2014-02-24
• Subjects: Psychophysiology -- Periodicals; 612.8
• DOI: 10.1111/psyp.12194
• Languages: English
• ISSNs: 0048-5772

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Little empirical evidence exists on the comparability of heart rate variability (HRV) quantification methods commonly used in infants. The aim was to compare three methods of HRV estimation: (1) fast Fourier transform (FFT), (2) autoregressive (AR), and (3) the Porges methods. HRV was estimated in 63 healthy 5‐month‐old infants. HRV parameters were strongly correlated across methods (.92–.99) but yielded significantly different mean HRV estimates (Porges method &gt; FFT &gt; AR). There was no systematic bias over the whole range of values between the two spectral approaches, while differences between the Porges method and the spectral estimates were systematically greater for larger values. Additional comparative studies are needed to explore the between‐method agreement across a range of physiological conditions.</p> </abstract>