Spectral Analysis of Congestive Heart Failure Cardiac Disease using Flexible Analytic Wavelet Transform

Heart rate variability (HRV) analysis has emerged as a widely utilized, non-invasive technique for evaluating the regulation of the cardiac autonomic system. Due to the intricate nature of the cardiovascular system, it cannot be accurately characterized by time or frequency domain analysis alone. The non-stationary nature of these signals necessitates the adoption of time-frequency methodologies that can capture and characterize the temporal changes in frequency components, enabling a more comprehensive understanding of heart rate variability. In this paper, a flexible analytical wavelet transform (FAWT) is proposed as a time-frequency analysis to capture the power spectra of the very low-frequency power (VLF), low-frequency power (LF), and high-frequency power (HF) component of the HRV signal for healthy and congestive heart failure (CHF) subjects. The findings indicate that healthy young subjects exhibit the lowest low-frequency to high-frequency power (LF/HF) ratio in comparison to healthy elderly persons and subjects with CHF diseases. The proposed work can be helpful to researchers and clinicians.