Detection of delay time between the alterations of cardiac rhythm and periodic breathing

Analysis of time-series multichannel physiological data were performed using wavelets. Wavelet provides a time-scale description and lead us to decompose any signal into frequency bands. A better precision in the frequency domain is often necessary to detect stationary phenomena or characterize time–frequency structures. A natural idea is to combine wavelet analysis with local Fourier analysis using an appropriate strategy: the wave packets. In this paper, we apply trigonometric wave packets to determine the time lag between the start of the apneas in the breathing and the consistent disorder in the cardiac rhythm. We show that breathing dynamic drives the evolution of the cardiac rhythm.