A Novel Approach in Heart-Rate-Variability Analysis Based on Modified Poincaré Plots

Abstract

This work involved human subjects in its research. Approval of all ethical and experimental procedures and protocols was granted by the Ethics Committee of the Medical Research Council (ETT-TUKEB) operating as a board of the Ministry of Human Capacities of Hungary under Approval No. IV/7109-1/2021/EKU, and performed in line with the WMA declaration of Helsinki.

Hierarchical organization of human physical activity

“…A notable result is that a proper parameter set (drift current, noise, upper threshold level) of the independent variables of the model could qualitatively reproduce the main statistic features describing the temporal organization of activity and rest periods. Note that the main difference between the models for nerve 31 or pacemaker heart cells 43 and HPA is that the ratio of the charging current and the noise is considerably smaller in the latter case, responsible for the strongly stochastic appearance of actograms: While I t /σ ≈ 20 in the heart-rate variability model, it is about 0.025 in this case.…”

“…However, a simple stochastic model that could account for the main observed features of human daily activity patterns until the moment has not been elaborated. We attempted to fill this gap by applying a modified noisy integrate-and-fire model, like the one applied for the simulation of stochastic features of other typical physiological signals, such as neuron firing or heart rhythms, as described in 31 , 43 . In a schematic, electronic representation of the model, a random noise (δ) is superimposed to a constant drift current (I t ) that is charging a capacitance (C), whose potential is short-cut by a discharge device (Fig.…”

“…Here, the drift current represents the “inner drive” leading to an elementary action (wrist motion), while the noise accounts for natural fluctuations, mainly due to the variable internal and external conditions. Since the original models using reflective boundary conditions 31 , 43 at the starting (“zero-current”) level were not able to reproduce the statistical properties of the measured actigraphy signals, we released the lower-bound conditions and allowed negative values for the driving current, as well, which may correspond to a sort of inhibition, similar to the hyperpolarization in nerve cells, in a lower level of hierarchy. Figure 5 B demonstrates the model-generated time series of spikes, while the results of a PDF analysis of the simulated signals, carried out as described under section 1 for the real HPA recordings, are shown in Fig.…”

Optimizing support vector machines and autoregressive integrated moving average methods for heart rate variability data correction

“…However, recently Búzás et al. [4] developed a method which might aid significantly in the analysis of HRV data measured during physical activity, during which HR increases and varies significantly compared to during rest.…”

Temporal Variation Measure Analysis: An Improved Second‐Order Difference Plot

“…Te nonlinear analyses are usually employed to analyze ECG since it refects a nonlinear characteristic of the biomedical signal. In numerous nonlinear analytical algorithms, the Poincaré plot analysis and the second-order diference plot analysis (SODP) are classical and often employed in the research of heart rate variability (HRV) [6][7][8][9][10][11][12][13][14][15][16].…”