Heart Rate Variability Trends Research Articles

Analyzing the effect of postural change on heart rate variability using multi-distance sample entropy (MDSE)

One of the most studied physiological measures is heart-rate variability. In this research paper, a new nonlinear method called Multi Distance Sample Entropy (MDSE) is proposed to accurately detect the variation of Heart rate variability (HRV) for different body postures and examine its effect on the activity of the autonomic nervous system. The proposed method used a multi-distance function to calculate the distance between other matched vector pairs. The goal of employing considerable distances is to investigate the distance aspect for enhancing the accuracy of recognizing the proper trend of HRV for the postural shift. Thus, the ECG signals of 55 participants were recorded in the supine posture for 10 min and similarly, for 10 min in the standing posture using the BIOPAC®MP36 system. The noise signals have been simulated for varieddata lengths, and their error bars have been plottedusing the proposed and conventional sample entropy (SE) methods to demonstrate the superiority of the proposed MDSE method over the SE. Afterward, the proposed method (MDSE) and other existing methods were applied to the recorded dataset. From the obtained results, it is clear that the proposed method can accurately detect the variation of HRV in supine and standing postures than other applied methods. Using the MDSE method, HRV trends are 6.91% more accurate than Conventional SE and 10.85% more accurate than approximation entropy (AE) for the recorded dataset. The Spearman rank correlation between proposed and applied nonlinear methods has also been evaluated.

Field Monitoring the Effects of Overnight Shift Work on Specialist Tactical Police Training with Heart Rate Variability Analysis

Police work exposes officers to high levels of stress. Special emergency response team (SERT) service exposes personnel to additional demands. Specifically, the circadian cycles of SERT operators are subject to disruption, resulting in decreased capacity to compensate in response to changing demands. Adaptive regulation loss can be measured through heart rate variability (HRV) analysis. While HRV Trends with health and performance indicators, few studies have assessed the effect of overnight shift work on HRV in specialist police. Therefore, this study aimed to determine the effects overnight shift work on HRV in specialist police. HRV was analysed in 11 SERT officers and a significant (p = 0.037) difference was found in pRR50 levels across the training day (percentage of R-R intervals varying by >50 ms) between those who were off-duty and those who were on duty the night prior. HRV may be a valuable metric for quantifying load holistically and can be incorporated into health and fitness monitoring and personnel allocation decision making.

Alteration of Autonomic Nervous System Is Associated With Severity and Outcomes in Patients With COVID-19.

BackgroundPrevious studies suggest that coronavirus disease 2019 (COVID-19) is a systemic infection involving multiple systems, and may cause autonomic dysfunction.ObjectiveTo assess autonomic function and relate the findings to the severity and outcomes in COVID-19 patients.MethodsWe included consecutive patients with COVID-19 admitted to the 21st COVID-19 Department of the east campus of Renmin Hospital of Wuhan University from February 6 to March 7, 2020. Clinical data were collected. Heart rate variability (HRV), N-terminal pro-B-type natriuretic peptide (NT-proBNP), D-dimer, and lymphocytes and subsets counts were analysed at two time points: nucleic-acid test positive and negative. Psychological symptoms were assessed after discharge.ResultsAll patients were divided into a mild group (13) and a severe group (21). The latter was further divided into two categories according to the trend of HRV. Severe patients had a significantly lower standard deviation of the RR intervals (SDNN) (P < 0.001), standard deviation of the averages of NN intervals (SDANN) (P < 0.001), and a higher ratio of low- to high-frequency power (LF/HF) (P = 0.016). Linear correlations were shown among SDNN, SDANN, LF/HF, and laboratory indices (P < 0.05). Immune function, D-dimer, and NT-proBNP showed a consistent trend with HRV in severe patients (P < 0.05), and severe patients without improved HRV parameters needed a longer time to clear the virus and recover (P < 0.05).ConclusionHRV was associated with the severity of COVID-19. The changing trend of HRV was related to the prognosis, indicating that HRV measurements can be used as a non-invasive predictor for clinical outcome.

Declining Trends of Heart Rate Variability According to Aging in Healthy Asian Adults.

Heart rate variability (HRV) indices correlate with aging and are related to the autonomic nervous system. However, the trend of HRV with age has not been explored for the Asian population. Therefore, we proposed a linear regression model of HRV indices that decreased with aging in healthy Asian adults. HRV parameters [High frequency (HF), Low frequency (LF), Very low frequency (VLF), Total power (TP), HRV triangular index (HRV-index), Standard deviation of the normal-to-normal interval (SDNN), and Proportion of normal-to-normal intervals greater than 50 ms (pNN50)] were measured in a total of 300 healthy participants (150 men and 150 women) aged 19–69 years stratified into five age groups: 19–29, 30–39, 40–49, 50–59, and 60–69 years comprising 60 people each in Seoul, South Korea. A simple regression analysis was performed to reveal the linear declining trend of HRV indices with age. Independent t-tests were conducted to investigate the gender differences in HRV values depending on each age group. The values of all HRV indices showed a decreasing trend with age in healthy Korean adults, as observed in the Western population (P < 0.001 for all indices); HF (Y = −0.039x + 6.833, R2 = 0.287), LF (Y = −0.047x + 7.197, R2 = 0.414), VLF (Y = −0.025x + 6.861, R2 = 0.177), TP (Y = −0.034x + 8.082, R2 = 0.352), HRV-index (Y = −0.125x + 15.628, R2 = 0.298), SDNN (Y = −0.502x + 53.907, R2 = 0.343), and pNN50 (Y = −0.650x + 53.852, R2 = 0.345) all decreased with age. There was no significant gender difference in any HRV parameter. A linear regression model of various HRV indices has been presented considering the age of healthy Asians, which may be useful to prevent diseases related to the autonomic nervous system by estimating or tracking autonomic functional degeneration in the Asian population.

Early Postnatal Heart Rate Variability in Healthy Newborn Infants.

BackgroundDespite the increasing interest in fetal and neonatal heart rate variability (HRV) analysis and its potential use as a tool for early disease stratification, no studies have previously described the normal trends of HRV in healthy babies during the first hours of postnatal life.MethodsWe prospectively recruited 150 healthy babies from the postnatal ward and continuously recorded their electrocardiogram during the first 24 h after birth. Babies were included if born in good condition and stayed with their mother. Babies requiring any medication or treatment were excluded. Five-minute segments of the electrocardiogram (non-overlapping time-windows) with more than 90% consecutive good quality beats were included in the calculation of hourly medians and interquartile ranges to describe HRV trends over the first 24 h. We used multilevel mixed effects regression with auto-regressive covariance structure for all repeated measures analysis and t-tests to compare group differences. Non-normally distributed variables were log-transformed.ResultsNine out of 16 HRV metrics (including heart rate) changed significantly over the 24 h [Heart rate p < 0.01; Standard deviation of the NN intervals p = 0.01; Standard deviation of the Poincaré plot lengthwise p < 0.01; Cardiac sympathetic index (CSI) p < 0.01; Normalized high frequency power p = 0.03; Normalized low frequency power p < 0.01; Total power p < 0.01; HRV index p = 0.01; Parseval index p = 0.03], adjusted for relevant clinical variables. We observed an increase in several HRV metrics during the first 6 h followed by a gradual normalization by approximately 12 h of age. Between 6 and 12 h of age, only heart rate and the normalized low frequency power changed significantly, while between 12 and 18 h no metric, other than heart rate, changed significantly. Analysis with multilevel mixed effects regression analysis (multivariable) revealed that gestational age, reduced fetal movements, cardiotocography and maternal chronic or pregnancy induced illness were significant predictors of several HRV metrics.ConclusionHeart rate variability changes significantly during the first day of life, particularly during the first 6 h. The significant correlations between HRV and clinical risk variables support the hypothesis that HRV is a good indicator of overall wellbeing of a baby and is sensitive to detect birth-related stress and monitor its resolution over time.

Respiratory sinus arrhythmia biofeedback therapy may increase heart rate variability activity and decrease reactivity in male patients with major depressive disorder: A pilot study

Objectives: Evidence suggests that depression is associated with a decreased trend of heart rate variability (HRV), which has been considered to be associated with unfavorable physical outcomes, and not resolved using various antidepressant medication treatments despite resolution of depression symptoms. In the present study, we intended to evaluate the effectiveness of HRV in respiratory sinus arrhythmia-biofeedback therapy (RSA-BT) on depression and HRV. Methods: We recruited 67 depressed male patients who received antidepressant or benzodiazepine treatments, received a psychological assessment, and were followed with a 3-week, 6-session RSA-BT. Results: After RSA-BT, HRV reactivity showed a significant mean decrease of 6.06 in low-frequency normal unit (p = 0.001) and 0.24 in the low-frequency/high-frequency (LF/HF) ratio (p

EMERGENCY MEDICINE RESIDENTS LACK THE NECESSARY AUTONOMIC NERVOUS SYSTEM BALANCE AND SHORT RELAXATION TECHNIQUES ARE INSUFFICIENT TO SOLVE THIS

Study objective. Heart rate variability (HRV) is an objective, easy-to-obtain parameter that can be used to monitor person’s balance of autonomous nervous system, which in turn decides one’s ability to cope with stress. HRV has been used extensively in professional athletes and the military with the purpose of performance optimisation and burnout prevention. The aim of our study was to investigate the balance of EM residents’ autonomic nervous system, as indicated by fluctuations in day-to-day HRV readings, and the feasibility of short relaxation techniques to increase their stress-resilience. Methods. We conducted a two-month long prospective cross-over double blinded randomized study. Computer randomization was used to divide the EM residents into intervention (A) and control (B) groups. Controls were instructed to listen to a 12 min. relaxation audio file every morning, while the intervention group was equipped with a 12 min. guided meditation that combined rhythmic breathing and attention focusing techniques. After one month, crossover of the interventions took place. Results. After pooling pre-shift and post-shift HRV data, we identified differences of statistical significance with post-shift HRV readings being higher (p=0.028, p&amp;lt;0,05). Individual HRV trend analysis showed significant fluctuations in day-to-day HRV readings. We could not identify the impact of short relaxation techniques on the EM residents HRV trends. Conclusion. Our findings suggest the lack of autonomic nervous system balance among EM residents, as indicated by big fluctuations in their day-to-day HRV trends. During the course of the study, the HRV reading fluctuations did not stabilise, indicating the limited use of our selected short relaxation techniques to increase residents’ stress resilience. We also identified paradoxical findings of higher post-shift HRV readings which could true be due to unique population in the setting of EM.

Dynamic psychophysiological correlates of a learning from text episode in relation to reading goals

This study aimed to investigate undergraduates' cardiac activity during an episode of complex learning from text. Specifically, we examined (a) heart rate (HR) and (b) heart rate variability (HRV) as psychophysiological measures while students read a science text and were tested on it. Reading goals were also taken into account: Students were asked to read for themselves to know more on a topic, or to read to perform well to gain course credit. Undergraduates (N = 50) were randomly assigned to one of the two reading goal conditions. Their HR and HRV were registered at baseline, while reading the text, during the testing phase, and while recovering from the task. Findings confirmed that in the condition with the reading goal focused on good performance, the students comprehended the text better than the students who read for themselves. Two mixed-effects models examined HR and HRV trends during the four phases of the learning episode. Findings showed a general trend in which students’ HRV was greater in the reading phase compared to baseline. HR decreased during reading and increased during the testing phase. This pattern indicates a deep cognitive effort of students while reading that gave way to higher psychophysiological arousal in the testing phase. Moreover, a series of linear regression models revealed that being under aroused and in a state of receptive calm during the reading phase allowed greater performance. Educational implications are drawn.

Exposure to Fine Particulate Matter Leads to Rapid Heart Rate Variability Changes

Introduction: Heart Rate Variability (HRV) reflects the adaptability of the heart to internal and external stimuli. Reduced HRV is a predictor of post-infarction mortality. We previously found in road maintenance workers HRV-increases several hours after exposure to fine particulate matter (PM2.5). This seemed to conflict with studies where PM-exposure acutely reduced HRV. We therefore assessed whether time from exposure to HRV-assessment could explain the differences observed. Methods: On five non-consecutive days, workers carried nephelometers providing 1-minute-interval PM2.5-exposure. Five-minute HRV-intervals of SDNN, (Standard Deviation of Normal to Normal beat intervals) and pNN50 (Percentage of the interval differences exceeding 50 milliseconds) were extracted from 24-hour electrocardiograms. Following 60 minutes PM2.5-exposure, changes in HRV-parameters were assessed during 120 minutes visually and by regression analysis with control for time at work, at home and during the night using autoregressive integrating moving average (ARIMA) models to account for autocorrelation of the time-series. Additional controls included changing the time windows and including body mass index (BMI) and age in the models. Result: Pattern analysis of 12,669 data points showed high modulation of mean, standard deviation (SD) and time trend of HRV (SDNN and pNN50) at low, and much reduced modulation at high PM2.5-exposures. The time trend following exposure was highly symmetrical, resembling a funnel plot. Regression analysis showed significant associations of decreasing SDNN and pNN50 (average, SD and absolute value of time trend) with increasing PM2.5-exposure, which remained significant when controlling for activity phases. Changing time windows did not change the pattern of response. Including BMI and age did not change the results. Conclusions: The reduced modulation of HRV following PM2.5-exposure is striking. It suggests strong interference with homeostatic controls. Such an interference would represent a serious bodily burden, and could help explain acute cardiac events. In this model, the increase of HRV several hours later would reflect a recovery response.

Mining Physiological Conditions from Heart Rate Variability Analysis

This article presents a successfully developed methodology for mining physiological conditions from heart rate variability (HRV) analysis. The application of HRV analysis in both research and clinical settings has seen rapid development in the past decades. Unlike previous research, this study employed features derived from longterm monitoring of HRV indices, as these trends can best reflect the autonomic nervous system dynamics influenced by various physiological conditions. We proposed two methods for mining physiological conditions from HRV trends: a decision-tree learning method and a hybrid learning method that combines feature selection, feature extraction, and classifier construction processes. The proposed methods have been validated through a clinical case study: severity classification for Parkinson's disease. Our approach yielded classification accuracy greater than 90.0%, and high sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV).

The Future of Acupuncture Moxibustion: A Transcontinental Three-Center Pilot Study Using High-Tech Methods

Background: Moxibustion is an Asian healing method that is able to achieve specific warming effects at acupoints. We discuss a new Japanese needle-moxa-system. Objective: To evaluate the effects of this new system in a transcontinental study using high-tech measuring methods. Design, Setting, and Participants: The study was conducted in 3 centers (Graz, Austria; Beijing, China; and Seoul, Korea). Beside basic technical temperature measurements in Seoul, 9 investigations were carried out in 6 healthy volunteers (3 women, 3 men; mean [SD] age, 27.2 [5.7] years) using different methods (thermography, laser Doppler flowmetry, laser Doppler imaging, and heart rate variability). Four persons were examined in Graz, 2 in Beijing. Intervention: Moxibustion was always applied at acupoint CV 6 (Qihai). In addition, biosignal registrations were carried out in Graz during painless laser acupuncture of acupoint CV 12 (Zhongwan). Main Outcome Measures: Changes in temperature, microcirculation, and heart rate. Results: Temperature distributions, changes in microcirculation (at isolated spots and as a large-area image), and trends of heart rate variability were registered. The dimensions of local and temporal effects of heat stimulation could be visualized objectively. Conclusions: Effects of the new moxibustion method can be quantified reliably by modern measuring equipment. Using this system, moxibustion under standardized conditions can be performed with a minimum of smoke emission and high degree of safety.

Interaction Effects of Ultrafine Carbon Black with Iron and Nickel on Heart Rate Variability in Spontaneously Hypertensive Rats

BackgroundParticulate matter (PM) has been reported to be associated with alterations in heart rate variability (HRV); however, the results are inconsistent. We propose that different components of PM cause the discrepancy.ObjectiveIn this study, our goal was to determine whether different types of exposure would cause different HRV effects, and to verify the interactions between co-exposing components.MethodsUltrafine carbon black (ufCB; 14 nm; 415 μg and 830 μg), ferric sulfate [Fe2(SO4)3; 105 μg and 210 μg], nickel sulfate (NiSO4; 263 μg and 526 μg), and a combination of high-dose ufCB and low-dose Fe2(SO4)3 or NiSO4 were intratracheally instilled into spontaneously hypertensive rats. Radiotelemetry data were collected in rats for 72 hr at baseline and for 72 hr the following week to determine the response to exposure. Effects of exposure on 5-min average of normal-to-normal intervals (ANN), natural logarithm-transformed standard deviation of the normal-to-normal intervals (LnSDNN), and root mean square of successive differences of adjacent normal-to-normal intervals (LnRMSSD) were analyzed using self-control experimental designs.ResultsBoth high- and low-dose ufCB decreased ANN marginally around hour 30, with concurrent increases of LnSDNN. LnRMSSD returned to baseline levels after small initial increases. We observed minor effects after low-dose Fe and Ni instillation, whereas biphasic changes were noted after high-dose instillations. Combined exposures of ufCB and either Fe or Ni resulted in HRV trends different from values estimated from individual-component effects.ConclusionsComponents in PM may induce different cardioregulatory responses, and a single component may induce different responses during different phases. Concurrent exposure to ufCB and Fe or Ni might introduce interactions on cardioregulatory effects. Also, the effect of PM may be mediated through complex interaction between different components of PM.

P-164 Trend of heart rate variability in patients treated with cardiac resynchronization therapy

P-164 Trend of heart rate variability in patients treated with cardiac resynchronization therapy

10.7 Heart rate variability trends in 90-minute period prior to onset of ventricular arrhythmias in ICD patients

10.7 Heart rate variability trends in 90-minute period prior to onset of ventricular arrhythmias in ICD patients

10.7 Heart rate variability trends in 90-minute period prior to onset of ventricular arrhythmias in ICD patients

�pattern in the V1 lead with the ST-segment elevation 0.2mV of a coved-type ECG was defined as “typical” Brugada-type ECG. Results: the Brugada-type ECG was found in 11 (10male) of 20387 children (0.054%, 95%CI: 0.022% to 0.086%). There was no child with typical Brugada-type ECG. The prevalence of Brugada-type ECG in male was significantly higher than that of female even in children (0.096% versus 0.010%, P=0.012), and was increased according to aging (first grader: 0.01%, fourth grader: 0.05%, seventh grader: 0.08%, tenth grader: 0.23%, p<0.008. ANOVA). Conclusions: the prevalence of Brugada-type ECG in Japanese children was much lower than that reported previously in adult population (0.7%) and was increased according to aging.

10.7 Heart rate variability trends in 90-minute period prior to onset of ventricular arrhythmias in ICD patients

10.7 Heart rate variability trends in 90-minute period prior to onset of ventricular arrhythmias in ICD patients

Dynamics extraction in multivariate biomedical time series.

A nonlinear analysis of the underlying dynamics of a biomedical time series is proposed by means of a multi-dimensional testing of nonlinear Markovian hypotheses in the observed time series. The observed dynamics of the original N-dimensional biomedical time series is tested against a hierarchy of null hypotheses corresponding to N-dimensional nonlinear Markov processes of increasing order, whose conditional probability densities are estimated using neural networks. For each of the N time series, a measure based on higher order cumulants quantifies the independence between the past of the N-dimensional time series, and its value r steps ahead. This cumulant-based measure is used as a discriminating statistic for testing the null hypotheses. Experiments performed on artificial and real world examples, including autoregressive models, noisy chaos, and nonchaotic nonlinear processes, show the effectiveness of the proposed approach in modeling multivariate systems, predicting multidimensional time series, and characterizing the structure of biological systems. Electroencephalogram (EEG) time series and heart rate variability trends are tested as biomedical signal examples.

Similar orthostatic defense in active, healthy young adult and late middle-aged men

Orthostatic defense is commonly validated with a 60 ° to 80 ° head-up tilt test, addressing the step response rather than the response to permanent orthostasis. During the initial phase of tilt, neural factors predominate, while later, the slower humoral factors fade in. It has been demonstrated that, during adaptation of the circulatory system to the standing conditions, overshoot and undershoot occur. These oscillations hamper straight-forward interpretation of a tilt test, and may contribute to the inconclusiveness of current studies regarding the aging of orthostatic defense. Gradual, progressive, orthostatic load testing seems a valuable alternative. We used a novel, incremental, head-up tilt protocol (0 ° to 80 °, 13 increments) to impose graded orthostatic stress on 46 healthy young adult men (mean age ±SD 25 ± 3 years), ana on 16 healthy late middle-aged men (60 ± 4 years), while recording the electrocardiogram and the blood pressure. A first-order estimate of the heart rate range associated with the sympathovagal transition was made by combined analysis of heart rate and heart rate variability trends. We observed similar responses in heart rate, heart rate variability, and blood pressure. Supine heart rate (61 ± 8 vs 61 ± 7 beats/min), heart rate at the maximal tilt angle (86 ± 13 vs 84 ± 12 beats/min), sympathovagal transition (112 ± 82 vs 111 ± 76 beats/min), percent increase of the rate-pressure product (49 ± 23% vs 43 ± 20%), and the slope of the linear regression of the mean blood pressure on the sine of the tilt angle (8.7 ± 8.3 vs 9.2 ± 7.1 mm Hg) did not differ significantly. We conclude that aging, per se, does not impair orthostatic defense under gradually increasing orthostatic stress.