Physical exercise is associated with parasympathetic withdrawal and increased sympathetic activity resulting in heart rate increase. The rate of post-exercise cardiodeceleration is used as an index of cardiac vagal reactivation. Analysis of heart rate variability (HRV) and complexity can provide useful information about autonomic control of the cardiovascular system. The aim of the present study was to ascertain the association between heart rate decrease after exercise and HRV parameters. Heart rate was monitored in 17 healthy male subjects (mean age: 20 years) during the pre-exercise phase (25 min supine, 5 min standing), during exercise (8 min of the step test with an ascending frequency corresponding to 70% of individual maximal power output) and during the recovery phase (30 min supine). HRV analysis in the time and frequency domains and evaluation of a newly developed complexity measure -sample entropy -were performed on selected segments of heart rate time series. During recovery, heart rate decreased gradually but did not attain pre-exercise values within 30 min after exercise. On the other hand, HRV gradually increased, but did not regain rest values during the study period. Heart rate complexity was slightly reduced after exercise and attained rest values after 30-min recovery. The rate of cardiodeceleration did not correlate with pre-exercise HRV parameters, but positively correlated with HRV measures and sample entropy obtained from the early phases of recovery. In conclusion, the cardiodeceleration rate is independent of HRV measures during the rest period but it is related to early postexercise recovery HRV measures, confirming a parasympathetic contribution to this phase.
Heart rate (HR) and heart rate variability (HRV) in newborns is influenced by genetic determinants, gestational and postnatal age, and other variables. Premature infants have a reduced HRV. In neonatal HRV evaluated by spectral analysis, a dominant activity can be found in low frequency (LF) band (combined parasympathetic and sympathetic component). During the first postnatal days the activity in the high frequency (HF) band (parasympathetic component) rises, together with an increase in LF band and total HRV. Hypotrophy in newborn can cause less mature autonomic cardiac control with a higher contribution of sympathetic activity to HRV as demonstrated by sequence plot analysis. During quiet sleep (QS) in newborns HF oscillations increase – a phenomenon less expressed or missing in premature infants. In active sleep (AS), HRV is enhanced in contrast to reduced activity in HF band due to the rise of spectral activity in LF band. Comparison of the HR and HRV in newborns born by physiological vaginal delivery, without (VD) and with epidural anesthesia (EDA) and via sectio cesarea (SC) showed no significant differences in HR and in HRV time domain parameters. Analysis in the frequency domain revealed, that the lowest sympathetic activity in chronotropic cardiac chronotropic regulation is in the VD group. Different neonatal pathological states can be associated with a reduction of HRV and an improvement in the health conditions is followed by changes in HRV what can be use as a possible prognostic marker. Examination of heart rate variability in neonatology can provide information on the maturity of the cardiac chronotropic regulation in early postnatal life, on postnatal adaptation and in pathological conditions about the potential dysregulation of cardiac function in newborns, especially in preterm infants.
The study of short-term cardiovascular interactions is classically performed through the bivariate analysis of the interactions between the beat-to-beat variability of heart period (RR interval from the ECG) and systolic blood pressure (SBP). Recent progress in the development of multivariate time series analysis methods is making it possible to explore how directed interactions between two signals change in the context of networks including other coupled signals. Exploiting these advances, the present study aims at assessing directional cardiovascular interactions among the basic variability signals of RR, SBP and diastolic blood pressure (DBP), using an approach which allows direct comparison between bivariate and multivariate coupling measures. To this end, we compute information-theoretic measures of the strength and delay of causal interactions between RR, SBP and DBP using both bivariate and trivariate (conditioned) formulations in a group of healthy subjects in a resting state and during stress conditions induced by head-up tilt (HUT) and mental arithmetics (MA). We find that bivariate measures better quantify the overall (direct + indirect) information transferred between variables, while trivariate measures better reflect the existence and delay of directed interactions. The main physiological results are: (i) the detection during supine rest of strong interactions along the pathway RR → DBP → SBP, reflecting marked Windkessel and/or Frank-Starling effects; (ii) the finding of relatively weak baroreflex effects SBP → RR at rest; (iii) the invariance of cardiovascular interactions during MA, and the emergence of stronger and faster SBP → RR interactions, as well as of weaker RR → DBP interactions, during HUT. These findings support the importance of investigating cardiovascular interactions from a network perspective, and suggest the usefulness of directed information measures to assess physiological mechanisms and track their changes across different physiological states.
Cardiovascular control acts over multiple time scales, which introduces a significant amount of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis has been developed to quantify the complexity of a time series over multiple time scales. In previous studies, MSE analyses identified impaired cardiovascular control and increased cardiovascular risk in various pathological conditions. Despite the increasing acceptance of the MSE technique in clinical research, information underpinning the involvement of the autonomic nervous system in the MSE of heart rate and blood pressure is lacking. The objective of this study is to investigate the effect of orthostatic challenge on the MSE of heart rate and blood pressure variability (HRV, BPV) and the correlation between MSE (complexity measures) and traditional linear (time and frequency domain) measures. MSE analysis of HRV and BPV was performed in 28 healthy young subjects on 1000 consecutive heart beats in the supine and standing positions. Sample entropy values were assessed on scales of 1-10. We found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position. The effect of orthostatic challenge on heart rate and blood pressure complexity depended on the time scale under investigation. Entropy values did not correlate with the mean values of heart rate and blood pressure and showed only weak correlations with linear HRV and BPV measures. In conclusion, the MSE analysis of heart rate and blood pressure provides a sensitive tool to detect changes in autonomic balance as induced by postural change.
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