The aim of this study was to examine the dependence of heart rate variability (HRV) measures on RR interval length and to find out relationships between linear and nonlinear measures. The spectral powers in very low (VLF), low (LF) and high (HF) frequency regions, short-term scaling exponent alpha(1) and sample entropy (SampEn) were determined. All spectral powers increased with increasing RR interval length until they reached a plateau. Neighbouring spectral powers were strongly correlated. The largest fraction of the spectrum consisted of VLF (from about 40 to 95%) and the smallest of HF, although HF was most sensitive to changes in RR interval length. SampEn is also increased with increasing RR interval, reaching a plateau. The dependence of alpha(1) on RR showed a deflection point at 0.5 s. Nonlinear measures can be expressed by spectral powers: alpha(1) by a linear function of ln(LF/HF) and SampEn by a quadratic function of ln HF. We concluded that during the day an increase of HR up to 120 beats min(-1) was reflected in a reduction in HF and LF and to a smaller extent in VLF and by decreased complexity and increased correlation in RR interval series. In sleep, HRV measures are at a plateau. We suggest that below intrinsic value, HR is regulated mainly by changes of parasympathetic activity, reflected in linear and nonlinear HRV measures.

We investigated cardio-respiratory coupling in patients with heart failure by quantification of bidirectional interactions between cardiac (RR intervals) and respiratory signals with complementary measures of time series analysis. Heart failure patients were divided into three groups of twenty, age and gender matched, subjects: with sinus rhythm (HF-Sin), with sinus rhythm and ventricular extrasystoles (HF-VES), and with permanent atrial fibrillation (HF-AF). We included patients with indication for implantation of implantable cardioverter defibrillator or cardiac resynchronization therapy device. ECG and respiratory signals were simultaneously acquired during 20 min in supine position at spontaneous breathing frequency in 20 healthy control subjects and in patients before device implantation. We used coherence, Granger causality and cross-sample entropy analysis as complementary measures of bidirectional interactions between RR intervals and respiratory rhythm. In heart failure patients with arrhythmias (HF-VES and HF-AF) there is no coherence between signals (p < 0.01), while in HF-Sin it is reduced (p < 0.05), compared with control subjects. In all heart failure groups causality between signals is diminished, but with significantly stronger causality of RR signal in respiratory signal in HF-VES. Cross-sample entropy analysis revealed the strongest synchrony between respiratory and RR signal in HF-VES group. Beside respiratory sinus arrhythmia there is another type of cardio-respiratory interaction based on the synchrony between cardiac and respiratory rhythm. Both of them are altered in heart failure patients. Respiratory sinus arrhythmia is reduced in HF-Sin patients and vanished in heart failure patients with arrhythmias. Contrary, in HF-Sin and HF-VES groups, synchrony increased, probably as consequence of some dominant neural compensatory mechanisms. The coupling of cardiac and respiratory rhythm in heart failure patients varies depending on the presence of atrial/ventricular arrhythmias and it could be revealed by complementary methods of time series analysis.

The origin of heart rate variability (HRV) is largely in parasympathetic activity. The direct influence of sympathetic activity and other control mechanisms, especially at an increased HR, is not well understood. The objectives of the study were to investigate the influence of increasing HR on the properties of heartbeat interval (RR) series in young healthy subjects. ECG was recorded in 9 trained and 11 untrained young men during supine rest, standing, incremental running exercise and relaxation. During exercise, a breath-to-breath gas exchange was monitored. The RR time series analysis included the spectral analysis, detrended fluctuations analysis method and sample entropy (SampEn) calculation. During exercise, spectral powers were reduced dramatically in both groups. The dependence of short-term scaling exponent (alpha(1)) on the RR included a characteristic maximum, while SampEn for the same value of the RR had a minimum. The value of HR corresponding to the maximum of alpha(1) and minimum of SampEn (IHR) corresponded to the intrinsic HR obtained by an autonomic blockade. In trained subjects, the curves alpha(1) versus RR and SampEn versus RR were moved toward larger RR, compared with control. For HR values higher than IHR, alpha(1) decreased and SampEn increased. These results reveal that the complexity of the heart rhythm above intrinsic HR decreases with an increase in HR. We suggest that at the highest HR intrinsic heart control is reflected in the heart rhythm. We point out the possibility of developing a new non-invasive method for the determination of intrinsic HR from the curve alpha(1) versus RR.

We examined the effects of gender and age in young and middle-aged subjects on the level of cardio-respiratory interaction by analyzing properties of cardiac, respiratory and cardiac-respiratory regulatory mechanisms under paced breathing. In 56 healthy subjects, ECG (RR interval) and respiratory signal were simultaneously acquired in supine position at paced (0.1-0.45 Hz, steps of 0.05 Hz) and spontaneous breathing. The participants were divided into gender matched group of young adults (19-25 years old) and middle-aged adults (35-44 years old). Power spectral analysis was applied on RR interval time series and spectral components in very low frequency (VLF), low frequency (LF) and high frequency (HF) ranges were computed. We also calculated sample entropy of RR interval series (SampEnRR), respiratory series (SampEnResp), and their cross-sample entropy (cross-SampEn). Under paced breathing, reduction of all spectral powers with age (p<0.05) is not gender dependent but reduction of some entropy measures is; SampEnRR and SampEnResp were lower only in men (p<0.05). In the middle-aged subjects, effect of gender on spectral measures is significant; males had lower HF (p < 0.05). Pattern of dependencies of SampEn and cross-SampEn on paced breathing frequency were significantly different in men (young vs. middle-aged, p = 0.001 and p = 0.037) and in middle-aged subjects (females vs. males, p = 0.011 and p = 0.008). In middle-aged males, lower entropy measures indicated reduced and less complex partial cardiac and respiratory control, and central cardio-respiratory control. In conclusion, in healthy middle-aged subjects changes in cardio-respiratory coupling are detectable only in males.

The aim of this study was to compare the dependence of heart rate variability (HRV) on heart period (RR interval length) under different physiological and pathological states in order to detect changes in HR modulation. The dependence of HRV on the RR interval length in healthy elderly subjects, congestive heart failure (CHF) patients and one patient with a transplanted heart (T) was compared with healthy young subjects. Spectral powers, sample entropy (SampEn) and short-term fractal scaling exponent (alpha1) were determined from 24 h free-running recordings. For the same HR, HRV measures were different in different groups. In healthy subjects HRV measures depended on RR interval length and all spectral powers were highly correlated, although reduced in elderly subjects. SampEn at high HR was the most sensitive quantity to changes induced by aging. In disease, CHF and T, an achievable HR range was decreased, all spectral powers were reduced, but correlated, and the dependence of HRV measures on RR was lost. There was an evident difference in the dependence of nonlinear on linear measures between young subjects and all the other studied groups. In disease the reduction in autonomic control was associated with the decrease in short-range correlation and regularity in RR series. We have concluded that the analysis of HRV measures as functions of RR interval length can reveal important aspects of HR control that might be lost in averaging.