Nonlinear coordination of cardiovascular autonomic control

Nonlinearities of heart rate variability in animal models of impaired cardiac control: contribution of different time scales

Heart rate variability (HRV) has been extensively explored by traditional linear approaches (e.g., spectral analysis); however, several studies have pointed to the presence of nonlinear features in HRV, suggesting that linear tools might fail to account for the complexity of the HRV dynamics. Even though the prevalent notion is that HRV is nonlinear, the actual presence of nonlinear features is rarely verified. In this study, the presence of nonlinear dynamics was checked as a function of time scales in three experimental models of rats with different impairment of the cardiac control: namely, rats with heart failure (HF), spontaneously hypertensive rats (SHRs), and sinoaortic denervated (SAD) rats. Multiscale entropy (MSE) and refined MSE (RMSE) were chosen as the discriminating statistic for the surrogate test utilized to detect nonlinearity. Nonlinear dynamics is less present in HF animals at both short and long time scales compared with controls. A similar finding was found in SHR only at short time scales. SAD increased the presence of nonlinear dynamics exclusively at short time scales. Those findings suggest that a working baroreflex contributes to linearize HRV and to reduce the likelihood to observe nonlinear components of the cardiac control at short time scales. In addition, an increased sympathetic modulation seems to be a source of nonlinear dynamics at long time scales. Testing nonlinear dynamics as a function of the time scales can provide a characterization of the cardiac control complementary to more traditional markers in time, frequency, and information domains.NEW & NOTEWORTHY Although heart rate variability (HRV) dynamics is widely assumed to be nonlinear, nonlinearity tests are rarely used to check this hypothesis. By adopting multiscale entropy (MSE) and refined MSE (RMSE) as the discriminating statistic for the nonlinearity test, we show that nonlinear dynamics varies with time scale and the type of cardiac dysfunction. Moreover, as complexity metrics and nonlinearities provide complementary information, we strongly recommend using the test for nonlinearity as an additional index to characterize HRV.

Oscillations of heart rate and respiration synchronize during affective visual stimulation

The objective of this study is to investigate the synchronization between breathing patterns and heart rate during emotional visual elicitation, that is, using sets of images gathered from the international affective picture system having five levels of arousal and five levels of valence, including a neutral reference level. Thirty-five healthy volunteers were emotionally elicited in agreement with a bidimensional spatial localization of affective states, i.e., arousal/valence plane, while two peripheral physiological signals, ECG and Respiration activity, were acquired simultaneously. The synchronization was then quantified by applying the concept of phase synchronization of chaotic oscillators, i.e., the cardio-respiratory synchrogram. This technique allowed us to estimate the synchronization ratio m:n as the attendance of n heartbeats in each m respiratory cycle, even for noisy and nonstationary data. We found a stronger evidence of cardiorespiratory synchronization during arousal than during neutral states.

A new heart rate variability analysis method by means of quantifying the variation of nonlinear dynamic patterns

A new heart rate variability (HRV) analysis method, quantifying the variation of nonlinear dynamic pattern (VNDP) in heart rate series, is proposed and validated against the age stratified Fantasia database. The method is based on three processes: (1) a recurrence quantification analysis (RQA) to quantify the dynamic patterns, (2) the use of mutual information (MI) and the entropy (EN) to characterize the VNDP, and 3) linear discriminant analysis to exploit the associations within MI and EN measures. Practically, the VNDP method overcomes the nonstationarity problem and exploits the nonstationary properties in HRV analyses. Physiologically, the VNDP reflects the properties of the fundamental short-term HRV dynamic system and the external associations of the system within the autonomous nervous system (ANS). The characteristic probability density peaks portrayed by VNDP plots indicate the quantum-like heart dynamics, which may provide valuable insights into the control of the ANS. The discrimination results of the reduced pattern dynamic range due to aging, from a new perspective, display the reduction in HRV. The significantly improved discriminatory power, compared to conventional RQA analyses, shows that the VNDP analysis can practically quantify the nonstationary nonlinear dynamics for ANS assessments.

A new algorithm developed based on a mixture of spectral and nonlinear techniques for the analysis of heart rate variability

In this paper, an algorithm based on a joint use of spectral and nonlinear techniques for heart rate variability (HRV) analysis is proposed. First, the measured RR data are passed into a trimmed moving average (TMA)-based filtering system to generate a lower frequency (LF) time series and a higher frequency (HF) one that approximately reflect the sympathetic and vagal activities, respectively. Since the Lyapunov exponent can be used to characterize the level of chaos in complex physiological systems, the largest Lyapunov exponents corresponding to the complex sympathetic and vagal systems are then estimated from the LF and HF time series, respectively, using an existing algorithm. Numerical results of a postural maneuver experiment indicate that both characteristic exponents or their combinations might serve as a set of innovative and robust indicators for HRV analysis, even under the contamination of sparse impulses due to aberrant beats in the RR data.

Life-threatening ventricular arrhythmia recognition by nonlinear descriptor

Background

Ventricular tachycardia (VT) and ventricular fibrillation (VF) are ventricular cardiac arrhythmia that could be catastrophic and life threatening. Correct and timely detection of VT or VF can save lives.

Methods

In this paper, a multiscale-based non-linear descriptor, the Hurst index, is proposed to characterize the ECG episode, so that VT and VF can be recognized as different from normal sinus rhythm (NSR) in the descriptor domain.

Results

This newly proposed technique was tested using MIT-BIH malignant ventricular arrhythmia database. The relationship between the ECG episode length and the corresponding recognition performance was studied. The experiments demonstrated good performance of the proposed descriptor. An accuracy rate as high as 100% was obtained for VT/VF to be recognized from NSR; for VT and VF to be recognized from each other, the recognition accuracy varies from 84.24% to 100%. In addition, the results were compared favorably against those obtained using Complexity measure.

Conclusions

There is strong potential for using the Hurst index for malignant ventricular arrhythmia recognition in clinical applications.

Effects of external periodic perturbations on short-term heart rate variability in healthy subjects and ischemic heart disease patients

AIMS

To characterise the frequency response of short-term heart rate variability to external periodic perturbations in healthy and ischemic heart disease subjects.

METHODS

Eleven healthy men and 11 ischemic heart disease patients were enrolled in this study. The frequency response of heart rate variability was assessed during periodic eyes opening test and controlled breathing at frequencies ranging from 0.08 to 0.25 Hz using autoregressive spectral analysis.

RESULTS

In subjects of both groups the mean heart rate and blood pressure were unchanged across experimental sessions. In healthy subjects eyes opening at rate of 8 and 6 times/min (0.12 and 0.10 Hz) evoked high-power peaks (P<0.05) at the same frequencies in the R-R power spectrum. The largest frequency response of heart rate variability was seen during eyes opening at 0.1 Hz (P<0.05). Ischemic heart disease patients failed to respond to periodic eyes opening with any changes in heart rate variability. During controlled breathing healthy subjects showed the highest heart rate variability frequency responses when breath frequency was 0.1 Hz (P<0.05). Comparatively, patients with ischemic heart disease had reduced frequency responses of heart rate variability at all breath rates and its magnitude did not depend on the perturbation frequency.

CONCLUSIONS

Our results demonstrate that the frequency response of short-term heart rate variability to external periodic perturbations is dependent on the perturbation frequency and the presence disease processes in the cardiovascular system.

Coupling patterns between spontaneous rhythms and respiration in cardiovascular variability signals

We performed a quantitative study of coupling patterns between respiration and spontaneous rhythms of heart rate and blood pressure variability signals by using the Recurrence Quantification Analysis (RQA). We applied RQA to both simulated and experimental data obtained in control breathing at three different frequencies (0.25, 0.20, and 0.13 Hz) from ten normal subjects. RQA succeeded in quantifying different degrees of non-linear coupling associated to several interference patterns. We found higher degrees of non-linear coupling when the respiratory frequency was close to the spontaneous Low Frequency (LF) rhythm (0.13 Hz), or almost twice the LF frequency (0.2 Hz), whereas weaker coupling was observed when the respiratory frequency was 0.25 Hz. Clinical applications of our approach should focus on new experimental protocols, featuring the stimulation of one of the two branches of the autonomic nervous system (ANS) or aimed at the analysis of pathologies linked to the ANS.

Transient phase locking patterns among respiration, heart rate and blood pressure during cardiorespiratory synchronisation in humans

The interactions between respiration, heart rate and blood pressure variability (HRV, BPV), are considered to be of paramount importance for the study of the functional organisation of the autonomic nervous system (ANS). The aim of the reported study is to detect and classify the intermittent phase locking (PL) phenomena between respiration, HRV and BPV during cardiorespiratory synchronisation experiments, by using the following time-domain techniques: Poincaré maps, recurrence plots, time-space separation plots and frequency tracking locus. The experimental protocol consists of three stages, with normal subjects in paced breathing at 15, 12 and 8 breaths min-1. Transient phenomena of coordination between respiration and the major rhythms of HRV and BPV (low and high frequency, LF and HF) have been detected and classified: no interaction between LF and HF rhythms at 15 breaths min-1; short time intervals of stable 1:2 frequency and phase synchronisation during the 12 breaths min-1 stage; 1:1 PL during the 8 breaths min-1 stage. 1:1 and 1:2 PL phenomena occurred when the respiration frequency was quite close to the LF frequency or when it was about twice the LF frequency, respectively. The complex organisation of the ANS seems to provoke transient rather than permanent PL phenomena between the co-ordinating components of respiration and cardiovascular variability series.

A new approach to uncover dynamic phase coordination and synchronization

Phase attractive maps are an essential mechanism of multi-stable systems such as found in coupled neuronal oscillators. An essential feature of this type of dynamic nonlinear coordination is dynamic phase synchronization. The identification of dynamic phase synchronizations is complicated due to changing frequency ratios of synchronized intervals, other nonstationarities, and noise. In order to overcome these problems the momentary phase relations and their statistics were analyzed by several authors. In this way phase synchronizations also in chaotic and noisy oscillating systems could be uncovered. We propose a novel method which avoids one essential limitation of these approaches, namely the necessity of presetting particular frequency ratios of interest. The proposed novel method was validated by its application to a simulated driven neuronal generator during the transition period between different synchronization modes and to dynamically coupled components of sympathetic nerve discharges.