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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 |
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| Authors: | Natalia Poliakova Ginette Dionne Etienne Dubreuil Blaine Ditto Robert O. Pihl Daniel Pérusse Richard E. Tremblay Michel Boivin |
| Affiliation: | 1. School of Psychology, Laval University, , Québec City, Québec, Canada;2. CHU de Québec Research Center, , Québec City, Québec, Canada;3. Department of Psychology, McGill University, , Montréal, Québec, Canada;4. Department of Anthropology, University of Montréal, Montréal, , Québec, Canada;5. Pediatrics, Psychiatry, and Psychology, University of Montréal, , Montreal, Québec, Canada;6. International Laboratory for Child and Adolescent Mental Health Development, INSERM U669, , Paris, France;7. School of Public Health and Population Science, University College Dublin, , Dublin, Ireland |
| 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: | Heart rate variability Methodological comparison Spectral analysis Fast Fourier transform Autoregressive analysis Porges method Infant |