scispace - formally typeset
Open AccessJournal ArticleDOI

Power spectral analysis of heart rate variability by autoregressive modelling and fast Fourier transform: a comparative study.

Reads0
Chats0
TLDR
Different methods for spectral decomposition of short-term heart rate variability yield similar qualitative results, but the quantitative results differ between ARM and FFT, and within the FFT method according to the selected frequency range.
Abstract
OBJECTIVE To compare the results from autoregressive modelling (ARM) and from fast Fourier transform (FFT), the most commonly used methods for the analysis of short-term heart rate variability in the frequency domain. METHODS & RESULTS RR interval and respiratory activity were recorded in the supine and standing positions under standardized laboratory conditions in a population-based sample of 614 subjects. The low-(LF) and high-frequency (HF) components of heart rate variability were identified by power spectral analysis, by use of FFT, with application of two sets of frequency ranges, and by ARM; LF and HF power were expressed in both normalized (%) and absolute units (ms2). The RR interval, its variance and the HF power decreased from the supine to the standing position (P < 0.001). The LF power increased on standing when expressed in normalized units, but decreased in absolute units, whereas the LF-to-HF ratio increased (P < 0.001). On the low side of the spectrum, FFT slightly overestimated the LF component obtained with ARM, when the predefined frequency range was 0.05-0.15 Hz (P < 0.001); the underestimation of LF in the frequency range 0.07-0.14 Hz was more pronounced, particularly in the erect position (P < 0.001). Both FFT methods overestimated (P < 0.001) the ARM HF component, more so for the 0.15-0.50 Hz range than for the 0.14-0.35 Hz range. Finally, we observed considerable within-subject differences between methods, which were estimated by calculation of the limits of agreement. CONCLUSIONS Different methods for spectral decomposition of short-term heart rate variability yield similar qualitative results, but the quantitative results differ between ARM and FFT, and within the FFT method according to the selected frequency range.

read more

Citations
More filters
Journal ArticleDOI

Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research - Recommendations for Experiment Planning, Data Analysis, and Data Reporting.

TL;DR: This paper will provide psychophysiological researchers with recommendations and practical advice concerning experimental designs, data analysis, and data reporting to ensure that researchers starting a project with HRV and cardiac vagal tone are well informed regarding methodological considerations in order for their findings to contribute to knowledge advancement in their field.
Journal ArticleDOI

Heart rate variability in athletes.

TL;DR: There is a strong need for basic research on the nature of the control and regulating mechanism exerted by the autonomic nervous system on cardiovascular function in athletes, preferably with a multidisciplinary approach between cardiologists, exercise physiologists, pulmonary physiologists and coaches and biomedical engineers.
Journal ArticleDOI

A quantitative systematic review of normal values for short-term heart rate variability in healthy adults

TL;DR: A need for large‐scale population studies and a review of the Task Force recommendations for short‐term HRV that covers the full‐age spectrum were identified, and a degree of homogeneity for common measures of HRV in healthy adults was shown across studies.
Journal ArticleDOI

Heart rate variability explored in the frequency domain: A tool to investigate the link between heart and behavior

TL;DR: The development of new non-linear approaches seems to provide a new perspective in investigating neural control of cardiovascular system as linear methodologies fail to provide significant information in conditions of extremely reduced variability.
Journal ArticleDOI

Heart rate variability: from bench to bedside.

TL;DR: Power spectrum analysis of cardiovascular signal variability, and in particular of the RR period (heart rate variability, HRV), is a widely used methodology for investigating autonomic neural regulation in health and disease that can quantify the sympathovagal balance modulating the sinus node pacemaker.
Related Papers (5)