Developing a mathematical model for the artificial generation of electrocardiogram (ECG) signals is a subject that has been widely investigated. One of its uses is for the assessment of diagnostic ECG signal processing devices. So the model should have the capability of producing a wide range of ECG signals, with all the nuances that reflect the sickness to which humans are prone, and this ...

We performed time-varying spectral analyses of heart rate variability (HRV) and blood pressure variability (BPV) recorded from 16 normal humans during acoustically induced arousals from sleep. Time-varying autoregressive modeling was employed to estimate the time courses of high-frequency HRV power, low-frequency HRV power, the ratio between low-frequency and high-frequency HRV power, and low-f...

The electrocardiogram (ECG) is a well known method that can be used to measure Heart Rate Variability (HRV). This paper describes a procedure for processing electrocardiogram signals (ECG) to detect Heart Rate Variability (HRV). In recent years, there have been wide-ranging studies on Heart rate variability in ECG signals and analysis of Respiratory Sinus Arrhythmia (RSA). Normally the Heart ra...

The principle difficulty with the analysis of the heart rate variability (HRV) is that heart rate dynamics are non-linear and non-stationary. Detrended fluctuation analysis (DFA) and correlation dimension (CD) are non-linear HRV measures to quantify fractal-like autocorrelation properties and to characterize the complex behaviour of nonlinear time series. Optimal ECG sampling rate is an importa...

Heart rate variability (HRV) is a measure of the balance between sympathetic mediators of heart rate that is the effect of epinephrine and norepinephrine released from sympathetic nerve fibres acting on the sino-atrial and atrio-ventricular nodes which increase the rate of cardiac contraction and facilitate conduction at the atrio-ventricular node and parasympathetic mediators of heart rate tha...

BACKGROUND Coronary Heart Disease (CHD) is the leading cause of death in many developed countries. The relation between heart rate variability (HRV) and CHD was recently explored after the development of HRV techniques. Lower HRV was proven to be associated with a greater risk for developing hypertension among normotensive men, and hypertension is one of the major risk factors of CHD. Acute myo...

Heart rate variability (HRV) analysis has quantified the functioning of the autonomic regulation of the heart and heart's ability to respond. However, majority of studies on HRV report several differences between patients with congestive heart failure (CHF) and healthy subjects, such as time-domain, frequency domain and nonlinear HRV measures. In the paper, we mainly presented a new approach to...

Processing of Heart Rate Variability (HRV) signal becomes more and more important for functional assessment of patient’s health. When developing Hybrid Models of cardiopulmonary system we need to make possible taking into account heart rate variability. Our aim is to generate signals that have properties similar to HRV in norm and in different pathologies. Hybrid models of cardiopulmonary syste...

BACKGROUND Major depressive disorder (MDD) is associated with increased heart rate and reductions in its variability (heart rate variability, HRV) - markers of future morbidity and mortality - yet prior studies have reported contradictory effects. We hypothesized that increases in heart rate and reductions in HRV would be more robust in melancholia relative to controls, than in patients with no...

In this paper, a new method for characterizing the newborn heart rate variability (HRV) is proposed. The central of the method is the newly proposed technique for instantaneous frequency (IF) estimation specifically designed for nonstationary multicomponent signals such as HRV. The new method attempts to characterize the newborn HRV using features extracted from the time–frequency (TF) domain o...