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

Psychophysiology. 2014 Jun;51(6):579-83. doi: 10.1111/psyp.12194. Epub 2014 Feb 24.

Abstract

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 > FFT > 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.

Keywords: Autoregressive analysis; Fast Fourier transform; Heart rate variability; Infant; Methodological comparison; Porges method; Spectral analysis.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Electrocardiography, Ambulatory
  • Female
  • Fourier Analysis*
  • Heart Rate / physiology*
  • Humans
  • Infant
  • Male
  • Monitoring, Physiologic