Volume 51, Issue 4

Aim: Heart rate variability (HRV) patterns reflect the changing effect of sympathetic and parasympathetic modulation of the autonomic nervous system. While overall and circadian heart rate (HR) and HRV are well characterized by traditional measures, there is currently no method to measure ultradian cycles of HR and HRV. Materials and methods: HR/HRV for each 2-min interval was calculated using normal-to-normal interbeat intervals from overnight polysomnographic ECGs in 113 subjects, aged 58±10 years (65 male, 48 female). HR, SDNN2, high-frequency power (HF) and the LF (low-frequency power)/HF ratio were plotted. A curve-fitting algorithm, developed in MatLab, identified cyclic patterns of HR/HRV and extracted parameters to characterize them. Results were compared for older vs. younger patients, males vs. females, with vs. without severe sleep apnea, and for the upper and lower half of sleep efficiency. Results: Ultradian patterns for different HR/HRV indices had variable correspondences with each other and none could be considered surrogates. Differences were seen for all comparison groups, but no one marker was consistently different across comparisons. Conclusion: Each HR/HRV parameter has its own rhythm, and the correspondence between these rhythms varies greatly across subjects. Quantification of ultradian patterns of HRV is feasible and could provide new insights into autonomic physiology.

We investigated whether body mass index and blood pressure have an additive influence on the carotid intima-media thickness (IMT). In 27 patients treated for hypertension (47.2±8.7 years) and 23 normotensive subjects (44.1±8.1 years), 24-h recording of blood pressure was performed. The carotid IMT was determined by ultrasonography and baroreflex sensitivity by a spectral method from 5-min recordings of blood pressure. Significant differences between hypertensive and normotensive subjects were observed for carotid IMT (0.60±0.08 vs. 0.51±0.07 mm; p<0.001) and baroreflex sensitivity (3.5±1.8 vs. 5.6±2.1 ms/mm Hg; p<0.001). Hierarchical multiple regression analysis (p<0.01) showed that carotid IMT was positively correlated with age (p<0.001) and body mass index (p<0.05) in normotensive subjects. The increased carotid IMT in hypertensive patients was not additively influenced by either age or body mass index. Baroreflex sensitivity decreased with age (p<0.01) and with carotid IMT (p<0.05) in normotensive subjects only. Multiregression analysis showed that an additive influence of age and body mass index on the development of carotid IMT is essential only in normotensive subjects. In hypertensive subjects the influence of blood pressure predominates, as documented by a comparison of the carotid IMT between hypertensive and normotensive subjects.

Within 5 years of first diagnosis, nearly 60% of patients with heart failure (HF) suffer from cardiac death. Early diagnosis of HF and reliable risk prediction are still required. Therefore, the objective of this study was to develop a parameter set for enhanced risk stratification in HF patients. In 43 patients suffering from HF (NYHA class ≥II, ejection fraction <45%) and 10 healthy subjects (REF), heart rate and blood pressure variability (HRV and BPV), interactions between heart rate and blood pressure (joint symbolic dynamics, JSD) and blood pressure morphology (BPM) were analysed. BPV, BPM and JSD measures revealed high significance (p<0.0001) in discriminating REF and HF. A set of three parameters from BPV, JSD and BPM was developed for risk stratification (sensitivity 76.5%, specificity 84.2%, area under the receiver operating characteristic curve 81.4%) in patients with HF.

Signals from different systems are analyzed during sleep on a beat-to-beat basis to provide a quantitative measure of synchronization with the heart rate variability (HRV) signal, oscillations of which reflect the action of the autonomic nervous system. Beat-to-beat variability signals synchronized to QRS occurrence on ECG signals were extracted from respiration, electroencephalogram (EEG) and electromyogram (EMG) traces. The analysis was restricted to sleep stage 2. Cyclic alternating pattern (CAP) periods were detected from EEG signals and the following conditions were identified: stage 2 non-CAP (2 NCAP), stage 2 CAP (2 CAP) and stage 2 CAP with myoclonus (2 CAP MC). The coupling relationships between pairs of variability signals were studied in both the time and frequency domains. Passing from 2 NCAP to 2 CAP, sympathetic activation is indicated by tachycardia and reduced respiratory arrhythmia in the heart rate signal. At the same time, we observed a marked link between EEG and HRV at the CAP frequency. During 2 CAP MC, the increased synchronization involved myoclonus and respiration. The underlying mechanism seems to be related to a global control system at the central level that involves the different systems.

We evaluated the role played by the autonomic nervous system in producing non-linear dynamics in short heart period variability (HPV) series recorded in healthy young humans. Non-linear dynamics are detected using an index of predictability based on a local non-linear predictor and a surrogate data approach. Different types of surrogates are utilized: (i) phase-randomized Fourier-transform based (FT) data; (ii) amplitude-adjusted FT (AAFT) data; and (iii) iteratively refined AAFT (IAAFT) data of two types (IAAFT-1 and IAAFT-2). The approach was applied to experimental protocols activating or blocking the sympathetic or parasympathetic branches of the autonomic nervous system or periodically perturbing cardiovascular control via paced respiration at different breathing rates. We found that short-term HPV was mostly linear at rest. Experimental protocols activating the sympathetic or parasympathetic nervous system did not produce non-linear dynamics. In contrast, paced respiration, especially at slow breathing rates, elicited significantly non-linear dynamics. Therefore, in short-term HPV (∼300 beats) the use of non-linear models is not supported by the data, except under conditions whereby the subject is constrained to a slow respiratory rate.

Coronary artery occlusions related to myocardial ischemia drive cardiac control system reactions that may lead to heart failure. The purpose of this study was to assess the autonomic nervous system (ANS) response during prolonged percutaneous transluminal coronary angioplasty (PTCA). Continuous ECG data were acquired from 50 patients before and during PTCA, with occlusions in the left anterior descending, left circumflex or right coronary artery. Heart rate variability (HRV) was analyzed for 3-min segments of the R-R interval signal obtained from ECG data. The ANS behavior was evaluated by HRV analysis using fractal-like indices. The fractal scalar exponent α 1 and power-law slope β decreased considerably during PTCA. This indicates that significant reactions of autonomic control of the heart rate occurred during coronary artery occlusions, with a reduction in complexity of the ANS.

Background : The cardiovascular control system is mediated by mechanisms acting at different time scales, such as heart period, vagal, sympathetic, and other slower controllers. Since these elements are interrelated in a complex manner, classical control theory fails and information-based description, based on autonomic information flow (AIF) functions, is appropriate. We investigated the hypothesis that AIF functions of typical time scales specifically characterize autonomic dysfunction and prognosis. Materials and methods : Holter recordings of patients with multiple organ dysfunction syndrome (MODS) (26 survivors, 10 non-survivors), heart failure (13 low risk, 13 high risk of cardiac arrest), idiopathic dilated cardiomyopathy (IDC) (26 low risk, 11 high risk), after abdominal aorta surgery (AAS) [32 with length of stay in hospital (LOS) >7 days; 62 with LOS ≤7 days] or with schizophrenia (n=20) were assessed and compared to 20 control subjects. Results : We found different AIF time scales discriminating risk. AIF measures of heart beat period had predominant prognostic value in heart failure patients, those of vagal communication in MODS and IDC, and those of long-term communication after AAS. Schizophrenic patients were discriminated from controls by vagally mediated communication. Conclusion : Different time scales of AIF represent specific pathophysiological aspects of altered complex autonomic control (communication) and consequently have predictive implications.

Heart rate variability (HRV) is a marker of autonomous activity in the heart. An important application of HRV measures is the stratification of mortality risk after myocardial infarction. Our hypothesis is that the information entropy of HRV, a non-linear approach, is a suitable measure for this assessment. As a first step, to evaluate the effect of myocardial infarction on the entropy, we compared the entropy to standard HRV parameters. The entropy was estimated by compressing the tachogram with Bzip2. For univariate comparison, statistical tests were used. Multivariate analysis was carried out using automatically generated decision trees. The classification rate and the simplicity of the decision trees were the two evaluation criteria. The findings support our hypothesis. The meanNN-normalized entropy is reduced in patients with myocardial infarction with very high significance. One entropy parameter alone exceeds the discrimination strength of multivariate standards-based trees.

In the context of HRV analysis, we evaluated the information content of two measures that can easily be derived from the classical RR time-domain indexes. The two measures are: 1) the ratio sd/rmssd, where sd is the RR standard deviation and rmssd is the root mean square of squared differences of consecutive RR beats; and 2) the ratio sd2/sd1, where sd2 and sd1 are extracted from the Poincaré plot and represent the transversal and longitudinal dispersion of the cloud of points ( RR i , RR i +1 ). We compared the performance of the two measures with that of the classical LF/HF ratio in a group of healthy subjects who underwent a 70° upright tilt test. The goodness of the results obtained by the two measures, the simplicity of their calculation and their applicability free from a priori assumptions on the characteristics of the data are proposed to the attention of the community involved in the HRV analysis as a possible alternative to the LF/HF ratio.

Background : Non-linear analysis of heart rate variability (HRV) can give additional information about autonomic control of the heart rate. This study applied the fractal dimension (FD) in a congestive heart failure (CHF) population. Methods : FD and HRV were evaluated in a healthy population (n=21) and an end-stage heart failure population (n=21) using 1-h segments during the day and night from Holter recordings. Results : CHF patients presented a loss of circadian variation in both FD and conventional time- and frequency-domain HRV indices. FD was higher in the CHF population both during the day and night. In the CHF population the correlation between FD and high-frequency power of HRV was lost. Conclusion : Day-night variations of heart rate fluctuations are lost in heart failure. Changes in FD reflecting physiological and pathophysiological changes were observed.

There is a lack of standard methods for the analysis of magnetocardiograms (MCGs). MCG signals have a shape similar to the ECG (P wave, QRS complex, T wave). High-quality multichannel recordings can indicate even slight disturbances of de- and repolarisation. The purpose of our study was to apply a new approach in the analysis of signal-averaged DC-MCGs. DC-MCGs (31-channel) were recorded in 182 subjects: 110 patients after myocardial infarction and 72 controls. Spatiotemporal correlation analysis of the QRS complex and T wave patterns throughout the entire heart cycle was used to analyse homogeneity of de- and repolarisation. These plots were compared to standard ECG analyses (electrical axis, Q wave, ST deviation, T polarity and shape). Spatiotemporal correlation analyses seem to be applicable in assessing the course of electrical repolarisation with respect to homogeneity. MCG provided all diagnostic information contained in common ECG recordings at high significance levels. The ECG patterns were included in 5/8 of our parameters for electrical axis, 6/8 for Q-wave, 7/8 for ST deviation and 5/8 for T-polarity based on two time series of correlation coefficients. We conclude that our spatiotemporal correlation approach provides a new tool for standardised analysis of cardiac mapping data such as MCG.

Heart rate variability (HRV) reflects regulatory processes of the cardiovascular system and reveals fractal characteristics. In this paper we investigated standard HRV parameters and scaling characteristics in ten athletes before, during, and after a 2-week training camp to assess the effects of short-term overtraining on cardiovascular control. High-resolution ECGs were recorded over 30 min under resting conditions 1 week before the training camp, after 1 week of training in the camp, and after 3–4 days of recovery. Standard HRV analysis was performed according to Task Force recommendations. Scaling characteristics were assessed, applying detrended fluctuation analysis (DFA). Standard HRV analysis showed significant changes in meanNN and rmssd during the training camp. DFA revealed three distinct regions of scale-invariance and significant alterations during the training camp. In conclusion, HRV might be used to monitor the training state in athletes.

Cardiac arrhythmia is currently investigated from two different points of view. One considers ECG biosignal analysis and investigates heart rate variability, baroreflex control, heart rate turbulence, alternans phenomena, etc. The other involves building computer models of the heart based on ion channels, bidomain models and forward calculations to finally reach ECG and body surface potential maps. Both approaches aim to support the cardiologist in better understanding of arrhythmia, improving diagnosis and reliable risk stratification, and optimizing therapy. This article summarizes recent results and aims to trigger new research to bridge the different views.

The coupled sino-atrial and atrio-ventricular nodes of the heart are discussed using a dedicated non-linear oscillator model. Several modes by which the oscillations cease in the system are obtained (asystole models). The oscillations of the model are compared with heart rate variability in heart block patients.

Long-term heart rate variability (HRV) series can be described by time-variant autoregressive modelling. HRV recordings show dependence between distant observations that is not negligible, suggesting the existence of long-range correlations. In this work, selective adaptive segmentation combined with fractionally integrated autoregressive moving-average models is used to capture long memory in HRV recordings. This approach leads to an improved description of the low- and high-frequency components in HRV spectral analysis. Moreover, it is found that in the 24-h recording of a case report, the long-memory parameter presents a circadian variation, with different regimes for day and night periods.

We assessed the clinical correlates of a comprehensive set of non-linear heart rate variability (HRV) indices computed from 24-h Holter recordings for 200 stable chronic heart failure (CHF) patients [median age (lower quartile, upper quartile) 54 (47, 58) years, LVEF 23% (19%, 28%)]. A total of 19 non-linear indices belonging to six major families, namely symbolic dynamics, entropy, empirical mode decomposition, fractality-multifractality, unpredictability and Poincaré plots, were considered. Most indices showed a significant association with ejection fraction and with the severity of symptoms, while only two (one each from the fractality and Poincaré plot families) showed an association with aetiology. Only one symbolic dynamics variable was associated with the presence of non-sustained ventricular tachycardia and two symbolic dynamics variables were associated with the rate of ventricular ectopic events. Our results demonstrate the existence of selective links between non-linear indexes of HRV and the clinical status and functional impairment of CHF patients. This indicates that further studies should be designed to investigate the physiopathological mechanisms involved in such links.

This study examines the utility of recurrence analysis in the field of sleep apnea detection from heart rate series. In 38 patients, ECGs were recorded during sleep in parallel to polysomnography (PSG). Parameters extracted from distance matrices and from recurrence plots (RPs) of the time-delay embedded RR series were tested for their suitability to detect minute-by-minute phases of sleep apnea by means of receiver operating curve (ROC) analysis against the findings of the PSG. Features derived from the continuous distance matrix yielded better results (sensitivity 77%; specificity 78%) than those quantifying the structure of the binary RP (67% and 74%, respectively), accentuating the significance of information on the magnitude of heart rate variations for sleep apnea detection. However, simpler and computationally less demanding spectral techniques yield largely comparable results (77% and 72%, respectively). This raises the question as to whether recurrence analysis of RR series yields additional insight into sleep apnea recognition from heart rate variations.

In this paper we use the concept of large-scale dimension densities to analyze heart rate variability data. This method uses a normalized Grassberger-Procaccia algorithm and estimates the dimension in the rather large scales of the system. This enables us to analyze very short data. First we reanalyze data from the CIC 2002 challenge and can completely distinguish between real data and computer-generated data using only one parameter. We then analyze unfiltered data for 15 patients with atrial fibrillation (AF), 15 patients with congestive heart failure (CHF), 15 elderly healthy subjects, and 18 young healthy subjects. This method can completely separate the AF group from the other groups and the CHF patients show significant differences compared to the young and elderly healthy volunteers. Furthermore, differences are evident in the dimensionality between day and night for healthy persons, but not for the CHF patients. Finally, the results are compared to standard heart rate variability parameters.

We investigated how the complexity of fetal heart rate fluctuations (fHRF) is related to the sleep states in sheep and human fetuses. The complexity as a function of time scale for fetal heart rate data for 7 sheep and 27 human fetuses was estimated in rapid eye movement (REM) and non-REM sleep by means of permutation entropy and the associated Kullback-Leibler entropy. We found that in humans, fHRF complexity is higher in non-REM than REM sleep, whereas in sheep this relationship is reversed. To show this relation, choice of the appropriate time scale is crucial. In sheep fetuses, we found differences in the complexity of fHRF between REM and non-REM sleep only for larger time scales (above 2.5 s), whereas in human fetuses the complexity was clearly different between REM and non-REM sleep over the whole range of time scales. This may be due to inherent time scales of complexity, which reflect species-specific functions of the autonomic nervous system. Such differences have to be considered when animal data are translated to the human situation.

Heart rate and blood pressure variability parameters were assessed to determine the risk of cardiac mortality in schizophrenia. We investigated 21 acute, unmedicated patients with paranoid schizophrenia and 21 matched controls. Cardiovascular parameters obtained included heart rate variability, blood pressure variability, cardiac output and left ventricular work index. All parameters investigated were analyzed using linear and non-linear techniques. These investigations revealed increased left ventricular work index and reduced heart rate variability. Furthermore, blood pressure was significantly higher compared to controls, whereas its variability was unchanged. We conclude that our results reflect autonomic cardiovascular dysregulation in acute schizophrenia.

Estimation of self-similarity is a promising tool for quantifying alterations in cardiovascular dynamics. To evaluate the as yet unexplored influence of sympathetic vascular regulation on the scaling exponent, namely on the parameter characterizing self-similarity, we studied patients with a spinal cord injury as a model of progressively impaired vascular control. We considered 24 able-bodied subjects (AB) and 23 paraplegics with increasing lesion levels: between T 12 and L 4 (n=7); T 5 and T 11 (n=9); and C 6 and T 4 (n=7). We recorded the heart rate in three conditions characterized by increasing sympathetic activation: supine (SUP), sitting (SIT) and exercise (EXE). We calculated the scaling exponent by detrended fluctuation analysis ( H DFA ). Sympathetic activation had different effects on H DFA , depending on the lesion level. H DFA tended to decrease in AB from SUP (0.85+0.02; mean+SEM) and SIT (0.84+0.02) to EXE (0.79+0.02). It remained constant in the T 12 –L 4 group (0.92+0.04, 0.94+0.05 and 0.94+0.04, respectively), while it increased significantly in the T 5 –T 11 group (0.88+0.07, 0.94+0.05, 1.00+0.08) and increased even more in the C 6 –T 4 group (0.83+0.07, 0.91+0.05, 1.06+0.06). Results suggest that heart-rate self-similarity depends on vascular sympathetic control, because it is altered by spinal-cord lesions, even when cardiac neural control is intact.

It is generally assumed that fetal heart rate variability increases with gestation, reflecting prenatal development of the autonomic nervous system. We examined standard measures quantifying fetal heart rate variability, as well as a complexity measure, approximate entropy, in 66 fetal magnetocardiograms recorded from 22 healthy pregnant women between the 16th and 42nd week of gestation. In particular, regularity in the fetal RR interval time series was assessed on the basis of symbolic dynamics. The results showed that, beside an overall increase in fetal heart rate variability and complexity during pregnancy, there was also an increase in specific sets of binary patterns with low approximate entropy, i.e., a high degree of regularity. These sets were characterized by short epochs of heart rate acceleration and deceleration, and comparison with surrogate data confirmed that their random occurrence is rare. The results most likely reflect the influence of increasingly differentiated fetal behavioral states and transitions between them in association with fetal development.

Intrauterine growth restriction (IUGR) remains a major problem in perinatal medicine because of the variety of its underlying causes and the prediction of its outcome. Characteristics of heartbeat interval patterns are associated with neuro-vegetative and humoral regulatory processes. Fetal magnetocardiography allows non-invasive assessment of these processes with high precision throughout the second half of gestation. The aim of our study was the analysis of linear and non-linear parameters of fetal heart rate fluctuations to distinguish between IUGR fetuses and a cohort of normal subjects, both pre-selected from heart-rate traces representing a quiet state of activity in the third trimester of gestation.

Interactions among physiological mechanisms are abundant in biomedical signals, and they may exist to maintain efficient homeostasis. For example, sympathetic and parasympathetic neural activities interact to either elevate or depress the heart rate to maintain homeostasis. There has been considerable effort devoted to developing algorithms that can detect interactions between various physiological mechanisms. However, methods used to detect the presence of interactions between the sympathetic and parasympathetic nervous systems, to take one example, have had limited success. This may be because interactions in physiological systems are non-linear and non-stationary. The goal of this work was to identify non-linear interactions between the sympathetic and parasympathetic nervous systems in the form of frequency and amplitude modulations in human heart-rate data (n=6). To this end, wavelet analysis was performed, followed by frequency analysis of the resultant wavelet decomposed signals in several frequency brackets we define as: very low frequency ( f <0.04 Hz), low frequency (0.04–0.15 Hz) and high frequency (0.15–0.4 Hz). Our analysis suggests that the high-frequency bracket is modulated by the low-frequency bracket in the heart rate data obtained in both upright and sitting positions. However, there was no evidence of amplitude modulation among these frequencies.

A method to evaluate the direction and strength of causal interactions in bivariate cardiovascular and cardiorespiratory series is presented. The method is based on quantifying self and mixed predictability of the two series using nearest-neighbour local linear approximation. It returns two causal coupling indexes measuring the relative improvement in predictability along direct and reverse directions, and a directionality index indicating the preferential direction of interaction. The method was implemented through a cross-validation approach that allowed quantification of directionality without constraining the embedding of the series, and fully exploited the available data to maximise the prediction accuracy. Validation on short simulated bivariate time series demonstrated the ability of the method to capture different degrees of unidirectional and bidirectional interaction. Moreover, application to representative examples of heart rate, systolic arterial pressure and respiration series allowed the inference of causal relationships related to known physiological mechanisms and experimental conditions.

Non-linear parameters were computed to assess the extent of spatial organization in the atria in terms of coupling/synchronization between electrograms recorded in different atrial sites. Recordings of 9 patients suffering from paroxysmal atrial fibrillation were tested during four clinical experimental conditions: sinus rhythm and atrial fibrillation, both before and after isoproterenol infusion, a drug mimicking adrenergic activation. Two non-linear metrics were investigated: an index of non-linear association (NLA) and a synchronization (S) index based on the cross-conditional entropy. Results evidence the presence of reduced coupling after drug infusion in both sinus rhythm and atrial fibrillation. Moreover, passing from the NLA to the S index, the capability of the parameter to capture the subtle changes due to isoproterenol administration increased.

Multiple organ dysfunction syndrome (MODS) is the failure of several organs after a trigger event. The mortality is high, at up to 70%. We hypothesize that autonomic dysfunction may substantially contribute to the development of MODS and speculate that there is an age dependence of autonomic dysfunction in MODS. A total of 90 consecutively admitted MODS patients were assigned to this study. Three variables of autonomic function were analyzed: heart rate variability (HRV), baroreflex sensitivity (BRS) and chemoreflex sensitivity (CRS). The patient cohort was divided into three age groups. The main finding was that BRS, CRS and almost all indices of HRV were attenuated in comparison to normal range data and there was no age dependence for HRV indices or CRS, but there was for BRS. In conclusion, autonomic function in MODS is attenuated. The influence of MODS on autonomic function overwhelms the age dependence of autonomic function observed in healthy subjects.

This study investigates the contribution of central vasopressin receptors in the modulation of systolic arterial pressure (SAP) and heart rate (HR) response to air-jet stress in conscious Wistar rats equipped with a femoral arterial catheter and intracerebroventricular cannula using novel non-peptide and selective vasopressin V 1a (SR49059) and V 1b (SSR149415) antagonists. The effects of stress on SAP and HR were evaluated by measuring the maximal response to stress, the latency of the maximal response, the duration of the recovery period, and the increase in the low frequency (LF) short-term variability component. Stress induced a parallel and almost immediate increase in both SAP and HR, followed by enhanced LF SAP variability in the recovery period. Pretreatment of rats with V 1a antagonist did not affect the maximal increase or the latency of SAP and HR response to acute stress, but shortened the recovery period of SAP and HR and prevented the increase in LF SAP. The V 1b antagonist reduced the maximal increase in SAP without affecting HR and their latencies, shortened the recovery period of SAP and inhibited the increase in LF SAP variability. These results indicate that both central V 1a and V 1b receptors mediate cardiovascular changes induced by air-jet stress in conscious rats.

The Poincaré plot is a widely used method for visualizing and calculating heart rate variability and for investigating the oscillatory nature of heart action. We show that the Poincaré plot produced using physiological data for RR intervals is asymmetric. This suggests that the processes of heart rate acceleration (shortening of consecutive RR intervals) and deceleration (prolongation of successive RR intervals) might be asymmetric. To investigate this phenomenon, we define descriptors quantifying the heart rate asymmetry and present the results of a study involving 5-min ECG recordings of 50 healthy subjects in which, despite of the shortness of the recordings, the asymmetry is clearly visible.