Wavelet-based analysis of human blood-flow dynamics (Q1286865)

The peripheral blood-flow signals, measured by the laser Doppler flow meter, were analyzed using the wavelet transform with the Morlet wavelet. This transform maps the signal from the time domain to the time-frequency domain. Its major advantage compared with the Fourier-based methods lies in the logarithmic time and frequency resolution. Thus, we were able to follow the time variations of frequency peaks in the range from 0.01 to 1 Hz. In this band, five characteristic peaks were found. The oscillations were characterized by time and spatial invariant measures. This dynamic approach can be used to reveal the physiological and pathophysiological properties of the mechanisms of cardiovascular control from the noninvasively measured signals. An illustration was given by comparing the blood flows, measured on two groups: a control group and a group of athletes. Several differences in the dynamics of the blood flow were found between these two groups, in addition to the difference in the median values of the flow. Using the dynamic approach, namely the wavelet transform, we were able to show that the increased blood flow in the trained subjects results from both the greater stroke volume and increased compliance of the peripheral vessels.