Time–frequency analysis of transient signals – application to cardiovascular control

A method for time–frequency decomposition (SDA) is presented for the analysis of cardiovascular signals, during steady state as well as under transient conditions. The SDA is applied to a simulated noisy non-stationary signal. It reliably discloses the time evolution of the different spectral components of the signal and does not present noise propagation as other time–frequency methods, such as Wigner–Ville distribution does. A comparison with the well-known short-time Fourier transform is also performed for non-stationary simulated signal showing that the SDA achieves a higher time–frequency resolution. Two physiological applications are then presented in which the SDA is used for the analysis of HR and BP variability, reflecting the activity of the autonomic nervous system. The power spectra of heart rate (HR) and blood pressure (BP) fluctuations during a change of posture from supine to standing are calculated. The decrease of vagal activity on standing is obvious and can be quantified from the spectrum of HR fluctuations. The increase in the LF fluctuations of both BP and HR spectra reflect the enhancement in sympathetic activity on standing. Finally, the power spectrum of fetal HR fluctuations is obtained by SDA. The respiratory peak is observed and can help in evaluating fetal well-being.