Chaotic global parameters correlation with heart rate variability in obese children

The aim of the study is to analyze heart rate dynamics in obese children by measures of HRV. HRV is a simple and non-invasive measure of autonomic impulses. 94 children of mixed gender aged eight to twelve years were divided into two equal groups based on body mass index: obese and normal weight range. HRV was monitored in the dorsal decubitus position for 20 minutes. After tests of normality, Kruskal Wallis was applied for the statistical analysis, with the level of significance set at (p < 0.05). Regarding the application of Principal Component Analysis the first two components represent 99.4% of total variance. The obese children exhibited in heart frequency dynamics associated to an increase in the Chaos Forward Parameter. The Chaos Forward Parameter which applies all three chaotic global parameters is suggested to be the most robust algorithm. Obesity in children can be termed a dynamical condition but it increases the chaotic response

HEART RATE DYNAMICS BY NOVEL CHAOTIC GLOBALS TO HRV IN OBESE YOUTHS

Objective: this study aimed to assess the heart rate dynamics in young obese subjects by novel chaotic globals to HRV. Methods: eighty-six young subjects were distributed in two equal groups (n = 43) according to the nutritional status: obese and control following Body Mass Index. For the analysis of HRV indexes, the heart rate was recorded heartbeat to heartbeat with the young resting in dorsal (prone) position for 30 minutes. Results: after Anderson-Darling and Lilliefors tests, the data was deemed non-normal. So, Kruskal-Wallis test of significance was applied for the statistical analysis, level set at (p < 0.01). Principal Component Analysis (PCA) identified two components represented 100% of total variance. The algorithm which applies all three parameters is suggested as the most influential and statistically very significant at the level (p < 0.001); it also elevates the chaotic response. Conclusion: youth obesity increases the chaotic response. The reasons for the study include quantitative assessment to allow effective dietary, pharmacological or even surgical intervention in the condition

Non-linear regulation of cardiac autonomic modulation in obese youths: Interpolation of ultra-short time series

Background. In this study, we applied ultra-short time series of interbeat intervals (RR-intervals) to evaluate heart rate variability through default chaotic global techniques with the purpose of discriminating obese youths from non-obese youth patients. Method. Chaotic global analysis of the RR-intervals from the electrocardiogram and pre-processing adjustments was undertaken. The effect of cubic spline interpolations was assessed, while the spectral parameters remained fixed. Exactly, 125 RR-intervals of data were recorded. Results. CFP1, CFP3, and CFP6 were the only significant combinations of chaotic globals when the standard conditions were enforced and at the level p<0.01 (or <1%). These significances were acheived via Kruskal–Wallis and Cohen’s ds effects sizes tests of significance after Anderson–Darling and Lilliefors statistical tests indicated non-normal distributions in the majority of cases. Adjustments of the cubic spline interpolation from 1 to 13 Hz were revealed to be inconsequential when measured by Kruskal–Wallis and Cohen’s ds, regarding the outcome between the two datasets. Conclusion. Chaotic global analysis was offered as a robust technique to distinguish autonomic dysfunction in obese youths. It can discriminate the two different groups using ultra-short data lengths, and no cubic spline interpolations need be applied

RISK APPRAISAL BY NOVEL CHAOTIC GLOBALS TO HRV IN SUBJECTS WITH MALNUTRITION

The aim of this study is to assess the risk of dynamical diseases in malnourished children. This is achieved by the application of novel chaotic global techniques to the RR-intervals of the electrocardiogram (ECG) in the cohort. Heart Rate Variability (HRV) is an inexpensive and non-invasive tool to measure the autonomic impulses. Here there has been a decrease in chaotic response of HRV. Seventy children were divided into equal groups and the HRV monitored for 20-25 minutes. The Chaos Forward Parameter (CFP) which applies all three chaotic global parameters is suggested to be the most robust algorithm. These three parameters are high spectral entropy (hsEntropy), high spectral detrended fluctuation analysis (hsDFA) and spectral multi-taper method (sMTM). hsEntropy is a function of the irregularity of amplitude and frequency of the power spectrums peaks. It is derived by applying Shannon entropy to the multi-taper method power spectrum. To derive hsDFA we calculate the spectral adaptation in exactly the same way as for hsEntropy using an adaptive multi-taper method power spectrum with the same settings; but DFA rather than Shannon entropy is the algorithm applied. sMTM is the area between the multi-taper method power spectrum and the baseline. After Anderson-Darling and Lilliefors tests of normality; Kruskal-Wallis was used for the statistical analysis, with the level of significance set at (p &lt; 0.01). Principal Component Analysis (PCA) identified two components representing 100% of total variance. Autonomic imbalance measured as HRV and an increased cardiovascular risk are described for overweight children as well as for malnourished and those with anorexia nervosa. The relationship between malnourishment and complexity measures is useful in the risk assessment of dynamical diseases associated with the condition. This is supportive in treatments, assisting the determination of the level of dietary or pharmacological intervention especially in related dynamical diseases

Heart rate variability analysis: Higuchi and Katz’s fractal dimensions in subjects with type 1 diabetes mellitus

Background and aims. Statistical markers are valuable when assessing physiological status over periods of time and in certain disease states. We assess if type 1 diabetes mellitus promote modification in the autonomic nervous system using the main two types of algorithms to estimate a Fractal Dimension: Higuchi and Katz. Material and methods. 46 adults were divided into two equal groups. The autonomic evaluation consisted of recording heart rate variability (HRV) for 30 minutes in supine position in absence of any other stimuli. Fractal dimensions ought then able to determine which series of interbeat intervals are derived from diabetics’ or not. We then equated results to observe which assessment gave the greatest significance by One-way analysis of variance (ANOVA1), Kruskal-Wallis technique and Cohen’s d effect sizes. Results. Katz’s fractal dimension is the most robust algorithm when assisted by a cubic spline interpolation (6 Hz) to increase the number of samples in the dataset. This was categorical after two tests for normality; then, ANOVA1, Kruskal-Wallis and Cohen’s d effect sizes (p≈0.01 and Cohen’s d=0.814143–medium effect size). Conclusion. Diabetes significantly reduced the chaotic response as measured by Katz’s fractal dimension. Katz’s fractal dimension is a viable statistical marker for subjectswith type 1 diabetes mellitus

Complex measurements of heart rate variability in obese youths: Distinguishing autonomic dysfunction

Introduction. Heart rate variability (HRV) can be assessed from RR-intervals. These are derived from an electrocardiographic PQRST-signature and can deviate in a chaotic or irregular manner. In the past, techniques from statistical physics have allowed researchers to study such systems.Objective. This study planned to assess the heart rate dynamics in young obese subjects by nonlinear metrics to heart rate variability. Method. 86 subjects were split equally according to status. Heart rate was recorded with the subjects resting in a dorsal (prone) position for 30 minutes. The complexity of the RR-intervals was assessed by five Entropies, Detrended Fluctuation Analysis, Higuchi and Katz’s fractal dimensions Following inconclusive tests of normality we calculated the One-Way Analysis of Variance, Kruskal-Wallis, and the Effect Sizes by Cohen’s d significances. Results. It was established that Shannon, Renyi and Tsallis Entropies and the Higuchi and Katz’s fractal dimensions could significantly discriminate the two groups. The three entropies were higher in obese youths, suggesting less predictable sets of RR intervals (p<0.0001; d≈1.0). Whilst the Higuchi (p<0.003; d≈0.76) and Katz’s (p≈0.02; d≈0.57) fractal dimensions were lower in obese youths. Conclusion. As with chaotic globals an increase in response was detected by three measures of entropy in young obese. This is counter to the decreasing response detected by fractal dimensions. Chaotic globals and entropies are more dependable than fractal dimensions when assessing the responses to obesity

Musical Auditory Stimulation and Cardiac Autonomic Regulation

Previous studies have already demonstrated that auditory stimulation with music influences the cardiovascular system. In this study, we described the relationship between musical auditory stimulation and heart rate variability. Searches were performed with the Medline, SciELO, Lilacs and Cochrane databases using the following keywords: “auditory stimulation”, “autonomic nervous system”, “music” and “heart rate variability”. The selected studies indicated that there is a strong correlation between noise intensity and vagal-sympathetic balance. Additionally, it was reported that music therapy improved heart rate variability in anthracycline-treated breast cancer patients. It was hypothesized that dopamine release in the striatal system induced by pleasurable songs is involved in cardiac autonomic regulation. Musical auditory stimulation influences heart rate variability through a neural mechanism that is not well understood. Further studies are necessary to develop new therapies to treat cardiovascular disorders

Auditory stimulation and cardiac autonomic regulation

Previous studies have already demonstrated that auditory stimulation with music influences the cardiovascular system. In this study, we described the relationship between musical auditory stimulation and heart rate variability. Searches were performed with the Medline, SciELO, Lilacs and Cochrane databases using the following keywords: "auditory stimulation", "autonomic nervous system", "music" and "heart rate variability". The selected studies indicated that there is a strong correlation between noise intensity and vagal-sympathetic balance. Additionally, it was reported that music therapy improved heart rate variability in anthracycline-treated breast cancer patients. It was hypothesized that dopamine release in the striatal system induced by pleasurable songs is involved in cardiac autonomic regulation. Musical auditory stimulation influences heart rate variability through a neural mechanism that is not well understood. Further studies are necessary to develop new therapies to treat cardiovascular disorders

Risk assessment of diabetes mellitus by chaotic globals to heart rate variability via six power spectra

Background: The priniciple objective here is to analyze cardiovascular dynamics in diabetic subjects by actions related to heart rate variability (HRV). The correlation of chaotic globals is vital to evaluate the probability of dynamical diseases. Methods. Forty-six adults were split equally. The autonomic evaluation consisted of recording HRV for 30 minutes in supine position without any additional stimuli. “Chaotic globals” are then able to statistically determine which series of interbeat intervals are diabetic and which are not. Two of these chaotic globals, spectral Entropy and spectral Detrended fluctuation analysis were derived from six alternative power spectra: Welch, Multi-Taper Method, Covariance, Burg, Yule-Walker and the Periodogram. We then compared results to observe which power spectra provided the greatest significance by three statistical tests: One-way analysis of variance (ANOVA1); Kruskal-Wallis technique and the multivariate technique, principal component analysis (PCA). Results: The Chaotic Forward Parameter One (CFP1) applying all three parameters is proven the most robust algorithm with Welch and MTM spectra enforced. This was proven following two tests for normality where ANOVA1 (p=0.09) and Kruskal-Wallis (p=0.03). Multivariate analysis revealed that two principal components represented 99.8% of total variance, a steep scree plot, with CFP1 the most influential parameter