Nonlinear cardio-respiratory interactions revealed by time-phase bispectral analysis

Abstract

Abstract. Bispectral analysis based on high order statistics, introduced recently as a technique for revealing time-phase relationships among interacting noisy oscillators, has been used to study the nature of the coupling between cardiac and respiratory activity. Univariate blood flow signals recorded simultaneously by laser-Doppler flowmetry on both legs and arms were analysed. Coupling between cardiac and respiratory activity was also checked by use of bivariate data and computation of the cross-bispectrum between the ECG and respiratory signals. Measurements were made on six healthy males aged 25-27 years. Recordings were taken during spontaneous breathing (20 min), and during paced respiration at frequencies both lower and higher than that of spontaneous respiration (either two or three recordings with a constant frequency in the interval between 0.09 and 0.35 Hz). At each paced frequency recordings were taken for 12 min. It was confirmed that the dynamics of blood flow can usefully be considered in terms of coupled oscillators, and demonstrated that interactions between the cardiac and respiratory processes are weak and time-varying, and that they can be nonlinear. Nonlinear coupling was revealed to exist during both spontaneous and paced respiration. When present, it was detected in all four blood flow signals and in the cross-bispectrum between the ECG and respiratory signal. The episodes with nonlinear coupling were detected in 11 out of 22 recordings and lasted between 19 s in the case of high frequency (0.34 Hz) and 106 s in the case of low frequency paced respiration (0.11 Hz).

The effect of low-frequency oscillations on cardio-respiratory synchronization

“…Next we need to deal with the couplings between the cardiac and respiration phases, . It is already established from the results of methods specifically developed for detecting the coupling directionality of interacting phases [26,27,[29][30][31], and with direct physiological observations, that respiration drives the heart more than the reverse. Moreover, these coupling terms should have perturbation characteristics comparable to natural frequencies ω 1,2 .…”

A Quadratic Nonlinear Prediction-Based Heart Motion Model following Control Algorithm in Robotic-Assisted Beating Heart Surgery

“…Specifically, the bi-spectral analysis examines the relationships between the oscillations at two basic frequencies, fr(respiration mode frequency), fh(heartbeat mode frequency) and 2fr, 2fh and a modulation component at the frequency fr ± fh and etc. [30] (a) Heart motion bi-spectrum mesh plot (b) Heart motion bi-spectrum contour plot Figure 3. Heart motion bi-spectrum plot Figure 3 presents a typical bi-spectrum for the whole frequency domain for heart motion signal.…”

Phase Statistics Approach to Time Series Analysis

“…The nature of the couplings has been extensively studied from measured data in recent years [4][5][6][7][8][9][10][11][12][13]. Recently, Schäfer et al [14,15] and Rosenblum et al [16] found that there were sufficiently long periods of hidden synchronization and concluded that the cardiorespiratory synchronization and respiratory sinus arrhythmia (RSA) are two competing factors in cardiorespiratory interactions.…”