Abstract
Heart rate variability (HRV) involves harmonic components and fractal components which are inversely proportional to their frequencies. The harmonic components with high frequency above 0.15Hz are associated with the respiratory cycle and reflect solely the parasympathetic activity, whereas the low frequency components below 0.15Hz are related to the baroreceptor reflex and are both sympathetically and parasympathetically mediated. The fractal components seem to have significant implication in the cardiovascular control center in the brain. However, their presence would result in the obscure harmonic components. Yamamoto and Hughson developed a useful spectral estimation method named the “Coarse-Graining Spectral Analysis (CGSA)” to selectively eliminate the fractal components. However, the CGSA method includes several incorrect processes in its algorithm. The present investigation proposes a corrected algorithm for eliminating the fractal components from HRV that is referred to as the “Fractal Decomposition of Power Spectrum (FDPS)”. It is clarified that the FDPS method is more sensitive to determine the harmonic components in HRV spectrum compared with the general spectral analysis. The proposed spectral analysis seems to be a useful way to assess the cardiovascular function particularly in elderly persons and patients with autonomic dysfunction whose HRV is reduced.
