Why the study?
Heart rate variability analysis is widely used for noninvasive assessment of regulatory systems, but the capabilities of the Hilbert-Huang method compared with standard Fourier analysis needed evaluation.
Does the Hilbert-Huang method provide different or improved spectral parameters for heart rate variability compared to Fourier analysis?
Does the Hilbert-Huang method provide different or improved spectral parameters for heart rate variability compared to Fourier analysis?
The Hilbert-Huang method offers a novel approach to heart rate variability spectral analysis by identifying 4 spectral components without fixed boundaries, potentially supplementing traditional Fourier analysis.
Answers are grounded in this paper and cite their sources.
Hilbert-Huang HRV spectral analysis may improve nonstationary signal resolution; leaves open clinical superiority over Fourier methods.
Analysis of heart rate variability (HRV) is widely used for noninvasive assessment of the state of its regulation systems. The aim of the research was to evaluate the capabilities of the Hilbert-Huang method for calculating spectral parameters of HRV in comparison with the commonly used Fourier analysis. Fourier analysis allows to estimate averaged spectral amplitudes and power of HRV oscillations in fixed frequency intervals, which are associated with the activity of sympathetic, parasympathetic and humoral regulation systems. Using the Hilbert-Huang method, we revealed 4 spectral components, described by Gauss functions, in which HRV oscillations are concentrated, and showed the absence of fixed boundaries between them. The obtained energy quantitative characteristics of the spectral components of heart rhythm oscillations can serve as the basis for diagnostic methods of its regulation, supplementing the commonly used ones.
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Гриневич et al. (2023) studied this question.
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