Spectral methods of heart rate variability analysis during dynamic exercise

Goncalo Vilhena Mendonca, Bo Fernhall, Kevin S. Heffernan, Fernando D. Pereira

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

To apply both autoregressive (AR) and fast Fourier transform (FFT) spectral analysis at rest, during two different dynamic exercise intensities and in recovery from maximal exercise and to compare raw and normalized powers obtained with both methods. Sixteen participants (age 22.3 ± 4.3 year) performed resting, submaximal and maximal protocols. The submaximal protocol consisted of two 5-min walks at 4 km h-1 at treadmill grades of 0 and 7.5%. Beat-to-beat R-R series were recorded. FFT and AR analyses were preformed on the same R-R series. Compared to AR, FFT provided higher total power (TP) and raw high-frequency (HF) power at rest and exercise. Furthermore, FFT LF/HF ratio was lower than with the AR, except under resting conditions. Both methods showed reductions in TP, raw HF and LF powers during exercise and recovery. Only the AR revealed a significant reduction for normalized HF power and increase for normalized LF power in transition from rest to exercise conditions. AR and FFT methods are not interchangeable at rest or during dynamic exercise conditions. The AR method is more sensitive to the effects of exercise on the normalized power spectra of heart rate variability (HRV) than FFT. Finally, as both approaches are equally insensitive to the increase of exercise relative intensity, there is no practical advantage of performing HRV spectral analyses by the AR or FFT at higher workloads.

Original languageEnglish (US)
Pages (from-to)237-245
Number of pages9
JournalClinical Autonomic Research
Volume19
Issue number4
DOIs
StatePublished - Aug 1 2009
Externally publishedYes

Keywords

  • Cardiac autonomic control
  • Dynamic exercise
  • Heart rate variability
  • Spectral analysis

ASJC Scopus subject areas

  • Endocrine and Autonomic Systems
  • Clinical Neurology

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