In this paper we assessed the possibility of using the pulse rate variability (PRV) extracted from the photoplethysmography signal as an alternative measurement of the HRV signal in non-stationary conditions. The study is based on analysis of the changes observed during a tilt table test in the heart rate modulation of 17 young subjects. First, the classical indices of HRV analysis were compared to the indices from PRV in intervals where stationarity was assumed. Second, the time-varying spectral properties of both signals were compared by time-frequency (TF) and TF coherence analysis. Third, the effect of replacing PRV with HRV in the assessment of the changes of the autonomic modulation of the heart rate was considered. Time-invariant HRV and PRV indices showed no statistically significant differences (p > 0.05) and high correlation (>0.97). Time-frequency analysis revealed that the TF spectra of both signals were highly correlated (0.99 +/- 0.01); the difference between the instantaneous power, in the LF and HF bands, obtained from HRV and PRV was small (<10(-3) s(-2)) and their temporal patterns were highly correlated (0.98 +/- 0.04 and 0.95 +/- 0.06 in the LF and HF bands, respectively) and TF coherence in the LF and HF bands was high (0.97 +/- 0.04 and 0.89 +/- 0.08, respectively). Finally, the instantaneous power in the LF band was observed to significantly increase during head-up tilt by both HRV and PRV analysis. These results suggest that although some differences in the time-varying spectral indices extracted from HRV and PRV exist, mainly in the HF band associated with respiration, PRV could be used as a surrogate of HRV during non-stationary conditions, at least during the tilt table test.

An assessment of the dynamic interactions between cardiovascular signals can provide valuable information to improve the understanding of cardiovascular control. In this study, two methodologies for the characterization of time-frequency (TF) coherence between cardiovascular signals are described. The methodologies are based on the smoothed pseudo-Wigner-Ville distribution (SPWVD) and multitaper spectrogram (MTSP), and include the automatic assessment of the significance level of coherence estimates. The capability to correctly localize TF regions, where signals are locally coupled, is assessed using computer-generated data, and data from healthy volunteers. The SPWVD allows for the localization of these regions with higher accuracy (AC > 96.9% for SNR ≥ 5 dB) than the MTSP (AC > 84.4% for SNR ≥ 5 dB). In 14 healthy subjects, TF coherence analysis was used to describe the changes, which a tilt table test provokes in the cardiovascular control. Orthostatic stress provoked an increase in the coupling between R-R variability (RRV) and systolic arterial pressure variability; it did not provoke any significant changes in the coupling between RRV and respiration. In HF band, it decreased the strength of the coupling between RRV and pulse interval variability estimated from arterial pressure signal.

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Interest in therapeutic applications of music has recently increased, as well as the effort to understand the relationship between music features and physiological patterns. In this study, we present a methodology for characterizing music-induced effects on the dynamics of the heart rate modulation. It consists of three steps: (i) the smoothed pseudo Wigner-Ville distribution is performed to obtain a time-frequency representation of HRV; (ii) a parametric decomposition is used to robustly estimate the time-course of spectral parameters; and (iii) statistical population analysis is used to continuously assess whether different acoustic stimuli provoke different dynamic responses. Seventy-five healthy subjects were repetitively exposed to pleasant music, sequences of Shepard tones with the same tempo as the pleasant music and unpleasant sounds overlaid with the same sequences of Shepard tones. Results show that the modification of HRV parameters are characterized by an early fast transient phase (15-20 s), followed by an almost stationary period. All kinds of stimuli provoked significant changes compared to the resting condition, while during listening to pleasant music the heart and respiratory rates were higher (for more than 80% of the duration of the stimuli, p < 10(-5)) and the power of the HF modulation was lower (for more than 70% of the duration of the stimuli, p < 0.05) than during listening to unpleasant stimuli.

Abstract-Objective: We propose two electrocardiogram (ECG)-derived markers of T-wave morphological variability in the temporal, dw, and amplitude, da, domains. Two additional markers, d NL w and d NL a , restricted to measure the non-linear information present within dw and da are also proposed. Methods: We evaluated the accuracy of the proposed markers in capturing T-wave time and amplitude variations in 3 situations: (1) In a simulated set up with presence of additive Laplacian noise, (2) when modifying the spatio-temporal distribution of electrical repolarization with an electro-physiological cardiac model and (3) in ECG records from healthy subjects undergoing a tilt table test. Results: The metrics dw, da, d NL w and d NL a followed T-wave time and amplitude induced variations under different levels of noise, were strongly associated with changes in the spatiotemporal dispersion of repolarization, and showed to provide additional information to differences in the heart rate, QT and Tpe intervals, and in the T-wave width and amplitude. Conclusion: The proposed ECG-derived markers robustly quantify T-wave morphological variability, being strongly associated with changes in the dispersion of repolarization. Significance: The proposed ECG-derived markers can help to quantify the variability in the dispersion of ventricular repolarization, showing a great potential to be used as arrhythmic risk predictors in clinical situations.

Impaired capacity to increase heart rate (HR) during exercise (ΔHRex), and a reduced rate of recovery post-exercise (ΔHRrec) are associated with higher cardiovascular mortality rates. Currently, the genetic basis of both phenotypes remains to be elucidated. We conduct genome-wide association studies (GWASs) for ΔHRex and ΔHRrec in ~40,000 individuals, followed by replication in ~27,000 independent samples, all from UK Biobank. Six and seven single-nucleotide polymorphisms for ΔHRex and ΔHRrec, respectively, formally replicate. In a full data set GWAS, eight further loci for ΔHRex and nine for ΔHRrec are genome-wide significant (P ≤ 5 × 10−8). In total, 30 loci are discovered, 8 being common across traits. Processes of neural development and modulation of adrenergic activity by the autonomic nervous system are enriched in these results. Our findings reinforce current understanding of HR response to exercise and recovery and could guide future studies evaluating its contribution to cardiovascular risk prediction.

forward to collaborating with Dr. Solaro in this new position and to welcoming his new editorial team to the journal.The Journal of Molecular and Cellular Cardiology publishes work advancing knowledge of the mechanisms responsible for both normal and diseased cardiovascular function. To this end papers are published in all relevant areas. These include (but are not limited to): structural biology; genetics; proteomics; morphology; stem cells; molecular biology; metabolism; biophysics; electrophysiology; pharmacology and physiology. Papers are encouraged with both basic and translational approaches. The journal is directed not only to basic scientists but also to clinical cardiologists who wish to follow the rapidly advancing frontiers of basic knowledge of the heart and circulation.

In this paper, an approach for heart rate variability analysis during exercise stress testing is proposed based on the integral pulse frequency modulation (IPFM) model, where a time-varying threshold is included to account for the nonstationary mean heart rate. The proposed technique allows the estimation of the autonomic nervous system (ANS) modulating signal using the methods derived for the IPFM model with constant threshold plus a correction, which is shown to be needed to take into account the time-varying mean heart rate. On simulations, this technique allows the estimation of the ANS modulation on the heart from the beat occurrence time series with lower errors than the IPFM model with constant threshold (1.1% ± 1.3% versus 15.0% ± 14.9%). On an exercise stress testing database, the ANS modulation estimated by the proposed technique is closer to physiology than that obtained from the IPFM model with constant threshold, which tends to overestimate the ANS modulation during the recovery and underestimate it during the initial rest.