To provide deeper insight into the dynamics and components of HRV’s more advanced, higher-order statistics, such as power spectral density (PSD) analysis, are applied. By definition, this analysis decomposes the heart rate signal into its frequency components and quantifies them in terms of their relative intensity, termed “power.” It provides estimates of the power spectrum density function of heart rate—that is, information on how overall HRV (variance of NN intervals or heart rates) is distributed as a function of frequency into different components. The algorithm used for this analysis is the fast Fourier transformation (FFT). The nonparametric approach of estimating frequency is used in the FFT algorithm. The window-based power spectrum density is calculated using the Hamming window, and the power spectrum is subsequently divided into three frequency bands: very low frequency (VLF; 0.001–0.04 Hz), low frequency (LF; 0.40–0.15 Hz), and high frequency (HF; 0.15–0.4). The FFT was calculated in the three preset frequencies, which were measured and calculated in square milliseconds and also in normalized units (NU). The total power spectral density was also calculated. These frequencies of the heart rhythm have the following physiological correlates: LF is mediated by sympathetic nervous system activity predominantly, whereas HF is mediated by parasympathetic nervous system activity predominantly.