Estimation Of Cardiorespiratory Nonlinear Couplings On The Basis Of RQA

The coupling of cardiovascular system and respiratory system is essential to maintain the whole life process. Although the two systems have their own rhythms, these rhythms are well synchronized via the central nervous system. A deep insight of the coupling of cardiovascular system and respiratory system is needed not only by understanding human physiology, but also by effort to investigate complex systems.The study of the oscillations in physiological systems and of the interactions between different oscillating sources has gained increasing attention over the last 20 years . In particular, the quantification of specific rhythms in short-term heart rate (HR) and blood pressure (BP) variability signals has been successfully used to investigate the autonomic nervous system (ANS) control processes . In this context, the most widely used method has been spectral analysis.In spite of the reliability of the power spectral analysis in estimating the harmonic contents of signals, this analysis can not be used to investigate non-linear interactions among different oscillating components. Further limitations of spectral analysis are stationarity constraints, which strongly affect spectral resolution, and the blindness to the phase information of signals. Evidences of transient non-linear interaction phenomena between respiration and cardiovascular variability signals collected so far by several studies have been attributed to the complex dynamics involving cardiovascular control. Thus, a deeper analysis based on differentsignal processing techniques is needed.In this investigation, we analyzed the interaction between cardiovascular and respiratory systems by means of a quantitative estimation of the degree of coupling based on the Recurrence Quantification Analysis (RQA). We performed a quantitative study of coupling patterns between respiration and spontaneous rhythms of heart rate and blood pressure variability signals by using the RQA. RQA methods were applied to experimental data obtained from 17 rabbits. The nonlinear coupling patterns of respiration-heart rate and respiration-blood pressure were observed before and after isoprenaline was used . we used three particular descriptors of theplot features-the percent recurrence (PR), the percentdeterminism (PD) and the entropy of recurrence (ER)--toevaluate different coupling patterns of the recurrence plot.We found higher degrees of non-linear coupling of respiration and cardiovascular variability signals after isoprenaline was used. The percent recurrence, the percent determinism and the entropy of recurrence were significantly different (P<0.05). RQA succeeded in quantifying different degrees of non-linear coupling associated to several interference patterns and is valuable in quantifying different degrees of non-linear coupling of respiration and cardiovascular variability signals.