Search

Objective: Numerous indices were devised for the statistical characterization of temporal dynamics of heart rate variability (HRV) with the aim to discriminate between healthy subjects and nonhealthy patients. Elaborating on the concepts of (multi)fractal and nonlinear analyses, the present contribution defines and studies formally novel non Gaussian multiscale representations., Methods: A methodological framework for non Gaussian multiscale representations constructed on wavelet p-leaders is developed, relying a priori neither on exact scale-free dynamics nor on predefined forms of departure from Gaussianity. Its versatility in quantifying the strength and nature of departure from Gaussian is analyzed theoretically and numerically. The ability of the representations to discriminate between healthy subjects and congestive heart failure (CHF) patients, and between survivors and nonsurvivor CHF patients, is assessed on a large cohort of 198 subjects., Results: The analysis leads to conclude that i) scale-free and multifractal dynamics are observed, both for healthy subjects and CHF patients, for time scales shorter than [Formula: see text]; ii) a circadian evolution of multifractal and non Gaussian properties of HRV is evidenced for healthy subjects, but not for CHF patients; iii) non Gaussian multiscale indices possess high discriminative abilities between survivor and nonsurvivor CHF patients, at specific time scales ([Formula: see text] and [Formula: see text])., Conclusions: The non Gaussian multiscale representations provide evidence for the existence of short-term cascade-type multifractal mechanisms underlying HRV for both healthy and CHF subjects. A circadian evolution of this mechanism is only evidenced for the healthy group, suggesting an alteration of the sympathetic-parasympathetic balance for CHF patients., Significance: Results obtained for a large cohort of subjects suggest that the novel non Gaussian indices might robustly quantify crucial information for clinical risk stratification in CHF patients.

Multifractal analysis of human heartbeat dynamics has been demonstrated to provide promising markers of Congestive Heart Failure (CHF). Yet, it crucially builds on the interpolation of RR intervals series, which has been generically performed with limited links to CHF pathophysiology. We devise a novel methodology estimating multifractal autonomic dynamics from heartbeat-derived series defined in the continuous time. We hypothesize that markers estimated from our novel framework are also effective for mortality prediction in severe CHF. We merge multifractal analysis within a methodological framework based on inhomogeneous point process models of heartbeat dynamics. Specifically, wavelet coefficients and wavelet leaders are computed over measures extracted from instantaneous statistics of probability density functions characterizing and predicting the time until the next heartbeat event occurs. The proposed approach is tested on data from 94 CHF patients, aiming at predicting survivor and non-survivor individuals as determined after a 4 years follow up. Instantaneous markers of vagal and sympatho-vagal dynamics display power-law scaling for a large range of scales, from s to s. Using standard SVM algorithms, the proposed inhomogeneous point-process representation based multifractal analysis achieved the best CHF mortality prediction accuracy of 79.11 % (sensitivity 90.48%, specificity 67.74%). Our results suggest that heartbeat scaling and multifractal properties in CHF patients are not generated at the sinus-node level, but rather by the intrinsic action of vagal short-term control and of sympatho-vagal fluctuations associated with circadian cardiovascular control, especially within the VLF band. These markers might provide critical information in devising a clinical tool for individualized prediction of survivor and non-survivor CHF patients.

Background: Atrial fibrillation (AF) is an identified risk factor for ischemic strokes (IS). AF causes a loss in atrial contractile function that favors the formation of thrombi, and thus increases the risk of stroke. Also, AF produces highly irregular and complex temporal dynamics in ventricular response RR intervals. Thus, it is hypothesized that the analysis of RR dynamics could provide predictors for IS. However, these complex and nonlinear dynamics call for the use of advanced multiscale nonlinear signal processing tools., Objectives: The global aim is to investigate the performance of a recently-proposed multiscale and nonlinear signal processing tool, the scattering transform, in predicting IS for patients suffering from AF., Methods: The heart rate of a cohort of 173 patients from Fujita Health University Hospital in Japan was analyzed with the scattering transform. First, p-values of Wilcoxon rank sum tests were used to identify scattering coefficients achieving significant (univariate) discrimination between patients with and without IS. Second, a multivariate procedure for feature selection and classification, the Sparse Support Vector Machine (S-SVM), was applied to predict IS., Results: Groups of scattering coefficients, located at several time-scales, were identified as significantly higher (p-value < 0.05) in patients who developed IS than in those who did not. Though the overall predictive power of these indices remained moderate (around 60 %), it was found to be much higher when analysis was restricted to patients not taking antithrombotic treatment (around 80 %). Further, S-SVM showed that multivariate classification improves IS prediction, and also indicated that coefficients involved in classification differ for patients with and without antithrombotic treatment., Conclusions: Scattering coefficients were found to play a significant role in predicting IS, notably for patients not receiving antithrombotic treatment. S-SVM improves IS detection performance and also provides insight on which features are important. Notably, it shows that AF patients not taking antithrombotic treatment are characterized by a slow modulation of RR dynamics in the ULF range and a faster modulation in the HF range. These modulations are significantly decreased in patients with IS, and hence have a good discriminant ability., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (Schattauer GmbH.)

A priori discrimination of high mortality risk amongst congestive heart failure patients constitutes an important clinical stake in cardiology and involves challenging analyses of the temporal dynamics of heart rate variability (HRV). The present contribution investigates the potential of a new multifractal formalism, constructed on wavelet p-leader coefficients, to help discrimination between survivor and non survivor patients. The formalism, applied to a high quality database of 108 patients collected in a Japanese hospital, enables to assess the existence of multifractal properties amongst congestive heart failure patients and to reveal significant differences in the multiscale properties of HRV between survivor and non survivor patients, for scales ranging from approximately 60 to 250 beats.

The present contribution aims at proposing a comprehensive and tutorial introduction to the practical use of wavelet Leader based multifractal analysis to study heart rate variability. First, the theoretical background is recalled. Second, practical issues and pitfalls related to the selection of the scaling range or statistical orders, minimal regularity, parabolic approximation of spectrum and parameter estimation, are discussed. Third, multifractal analysis is connected explicitly to other standard characterizations of heart rate variability: (mono)fractal analysis, Hurst exponent, spectral analysis and the HF/LF ratio. This review is illustrated on real per partum fetal ECG data, collected at an academic French public hospital, for both healthy fetuses and fetuses suffering from acidosis.

Aims: Velocity changes in the solar wind, recorded by satellite (IMP8 and Wind) are characterized by a solar cycle dependent approximately 1.3-year component. The presence of any approximately 1.3-year component in human blood pressure (BP) and heart rate (HR) and in mortality from myocardial infarction (MI) is tested and its relative prominence compared to the 1.0-year variation., Materials and Methods: Around the clock manual or automatic BP and HR measurements from four subjects recorded over 5 to 35 years and a 29-year record of mortality from MI in Minnesota were analyzed by linear-nonlinear rhythmometry. Point and 95% confidence interval (CI) estimates were obtained for the approximately 1.3-year period and amplitude. The latter is compared with the 1.0-year amplitude for BP and HR records concurrent to the solar data provided by one of us (JDR)., Results: An approximately 1.3-year component is resolved nonlinearly for MI, with a period of 1.23 (95% CI: 1.21; 1.26) year. This component was invariably validated with statistical significance for BP and HR by linear rhythmometry. Nonlinearly, the 95% CI for the 1.3-year amplitude did not overlap zero in 11 of the 12 BP and HR series. Given the usually strong synchronizing role of light and temperature, it is surprising that 5 of the 12 cardiovascular series had a numerically larger amplitude of the 1.3-year versus the precise 1.0-year component. The beating of the approximately 1.3-year and 1.0-year components was shown by gliding spectra on actual and simulated data., Discussion and Conclusion: The shortest 5-year record (1998-2003) revealed an approximately 1.3-year component closer to the solar wind speed period characterizing the entire available record (1994-2003) than that for the concurrent 5-year span. Physiological variables may resonate with non-photic environmental cycles that may have entered the genetic code during evolution.

In several human adults, certain solar activity rhythms may influence an about 7-day rhythm in heart rate. When no about-weekly feature was found in the rate of change in sunspot area, a measure of solar activity, the double amplitude of a circadian heart rate rhythm, approximated by the fit of a 7-day cosine curve, was lower, as was heart rate corresponds to about-weekly features in solar activity and/or relates to a sunspot cycle.