Asymmetric properties of long-term and total heart rate variability

We report on two new physiological phenomena: the long-term and total heart rate asymmetry, which describe a significantly larger contribution of heart rate accelerations to long-term and total heart rate variability. In addition to the existing pair of indices, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {SD1}}_{\rm d}, {\text {SD1}}_{\rm a},$$\end{document} which are based on partitioning short-term variance, we introduce two other pairs of descriptors based on partitioning long-term (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {SD2}}_{\rm d}, {\text {SD2}}_{\rm a}$$\end{document}) and total (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text {SDNN}}_{\rm d}, {\text {SDNN}}_{\rm a}$$\end{document}) heart rate variability. The new asymmetric descriptors are used to analyze RR intervals time series derived from the 30-min ECG recordings of 241 healthy subjects resting in supine position. It is shown that both new types of asymmetry are present in 76% of the subjects. The new phenomena reported here are real physiological findings rather than artifacts of the method since they vanish after data shuffling

Mood Disorder Detection in Adolescents by Classification Trees, Random Forests and XGBoost in Presence of Missing Data

We apply tree-based classification algorithms, namely the classification trees, with the use of the rpart algorithm, random forests and XGBoost methods to detect mood disorder in a group of 2508 lower secondary school students. The dataset presents many challenges, the most important of which is many missing data as well as the being heavily unbalanced (there are few severe mood disorder cases). We find that all algorithms are specific, but only the rpart algorithm is sensitive; i.e., it is able to detect cases of real cases mood disorder. The conclusion of this paper is that this is caused by the fact that the rpart algorithm uses the surrogate variables to handle missing data. The most important social-studies-related result is that the adolescents’ relationships with their parents are the single most important factor in developing mood disorders—far more important than other factors, such as the socio-economic status or school success

Measures of Heart Rate Variability in 24-h ECGs Depend on Age but Not Gender of Healthy Children

Many methods computing heart rate variability (HRV) have been applied in studies in children. Not all of these methods have a comprehensive physiological interpretation, and not all of studies are in agreement with the Task Force Standards on HRV from 1996, and the New Joint Position Statement on the advances of HRV from 2015. The study aim was to analyse HRV in the 24-h ECGs of healthy children by the Poincare plots and Lomb-Scargle periodograms, and to follow proper HRV recommendations. Additionally, we investigated the associations between age, children's sex and measured HRV indices. One hundred healthy children, aged 3–18 underwent 24-h ECG Holter monitoring. HRV was analyzed by the Poincaré plots and spectral by Lomb-Scargle periodograms of RR intervals. The Mann-Whitney test was used to compare sex differences in HRV, the van Elteren's test was used to correct for the age-gender interaction, and non-parametric Spearman correlation was applied to analyse the association between age and HRV indices. None of the HRV measures differed significantly between boys and girls. None of the HRV indices was modified by the age-gender interaction. There were statistically significant associations of age with measures of ultra-low (rho = 0.42; p < 0.0001), very low (rho = 0.35; p = 00004) and low (rho = 0.30; p = 0.0028) frequency powers, the ratio of the low to high frequency power (rho = 0.38; p = 0.0001), indices of long-term (SD2; rho = 0.37; p = 0.0002) and total (SDNN; rho = 0.33; p = 0.0008) HRV, and the contribution of the long-term HRV to total HRV (CL; rho = 0.32; p = 0.0012). In general, HRV parameters derived from the analyses of Poincaré plots and Lomb-Scargle periodograms appear not to be affected by gender, however, most of them increase with age in the 24-h ECG recordings in healthy children

Bootstrapping the empirical bounds on the variability of sample entropy in 24-hours ECG recordings for 1 hour segments

We investigate the variability of one of the most often used complexity measures in the analysis of the time series of RR intervals, i.e. Sample Entropy. The analysis is carried out for a dense matrix of possible r thresholds in 79 24h recordings, for segments consisting of 5000 consecutive beats, randomly selected from the whole recording. It is repeated for the same recordings in random order. This study is made possible by the novel NCM algorithm which is many orders of magnitude faster than the alternative approaches. We find that the bootstrapped standard errors for Sample entropy are large for RR intervals in physiological order compared to the standard errors for shuffled data which correspond to the maximum available entropy. This result indicates that Sample Entropy varies widely over the circadian period. This paper is purely methodological and no physiological interpretations are attempted