Short-term heart rate variability—age dependence in healthy subjects

Cardiac Autonomic Neuropathy in Graves' Disease: Smoking and Age as Predictive Factors

OBJECTIVES

Hypermetabolic state in Graves' disease (GD) has a great impact on heart homeostasis, acting directly on the heart muscle and modulating the autonomic nervous system. To characterize cardiac autonomic neuropathy (CAN) as a possible complication in patients with GD.

METHODS

We evaluated euthyroid GD patients and a control group of healthy euthyroid people. CAN was assessed using autonomic tests of cardiovascular reflex and heart rate variability: respiratory, Valsalva, orthostatic and orthostatic hypotension tests, high frequency, low frequency, and very low-frequency bands. Transthoracic echocardiography was performed in GD patients.

RESULTS

Sixty GD patients and 50 people in control group were assessed. CAN was diagnosed in 20% of GD and 14% in the control group. Among GD, 13.3% presented incipient, and 6.7% established CAN, while in the control group, it was verified incipient in 8% and established in 6% (P = .7479). All GD patients with CAN presented an alteration in the deep breathing test. Age and smoking were evidenced as factors associated with the presence of CAN, while higher TRAb values at diagnosis decreased the chance of CAN.

CONCLUSIONS

The prevalence of CAN in euthyroid GD patients was 20%. Changes in the cardiac autonomic nervous system were identified, pointing to the importance of evaluating this complication in these patients. Smoking was a predictive factor for CAN, increasing its relationship with conditions that aggravate GD.

Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science

This updated guideline replaces the "Guideline for the application of heart rate and heart rate variability in occupational medicine and occupational health science" first published in 2014. Based on the older version of the guideline, the authors have reviewed and evaluated the findings on the use of heart rate (HR) and heart rate variability (HRV) that have been published in the meantime and incorporated them into a new version of this guideline.This guideline was developed for application in clinical practice and research purposes in the fields of occupational medicine and occupational science to complement evaluation procedures with respect to exposure and risk assessment at the workplace by the use of objective physiological workload indicators. In addition, HRV is also suitable for assessing the state of health and for monitoring the progress of illnesses and preventive medical measures. It gives an overview of factors influencing the regulation of the HR and HRV at rest and during work. It further illustrates methods for measuring and analyzing these parameters under standardized laboratory and real workload conditions, areas of application as well as the quality control procedures to be followed during the recording and evaluation of HR and HRV.

Heart rate and heart rate variability in obsessive-compulsive disorder: Evidence from patients and unaffected first-degree relatives

Altered heart rate (HR) and heart rate variability (HRV) are common observations in psychiatric disorders. Yet, few studies have examined these cardiac measures in obsessive-compulsive disorder (OCD). The current study aimed to investigate HR and HRV, indexed by the root mean square of successive differences (RMSSD) and further time domain indices, as putative biological characteristics of OCD. Electrocardiogram was recorded during a five-minute resting state. Group differences between patients with OCD (n = 96), healthy participants (n = 112), and unaffected first-degree relatives of patients with OCD (n = 47) were analyzed. As potential moderators of group differences, we examined the influence of age and medication, respectively. As results indicated, patients with OCD showed higher HR and lower HRV compared to healthy participants. These group differences were not moderated by age. Importantly, subgroup analyses showed that only medicated patients displayed lower HRV compared to healthy individuals, while HR alterations were evident in unmedicated patients. Regarding unaffected first-degree relatives, group differences in HRV remained at trend level. Further, an age-moderated group differentiation showed that higher HRV distinguished relatives from healthy individuals in young adulthood, whereas at higher age lower HRV was indicative of relatives. Both the role of familial risk and medication in HRV alterations need further elucidation. Pending future studies, alterations in HR and potentially HRV might serve as useful indices to characterize the pathophysiology of OCD.

Mediating Effect of Heart Rate Variability on the Relationship Between Anxiety Symptoms and Blood Pressure in Patients with Primary Hypertension

Patients with hypertension (HTN) are at increased risk of developing cardiovascular disease, which can be reduced with blood pressure (BP) control. Anxiety can contribute to high BP and low heart rate variability (HRV). Although relationships between social support, self-rated health-status (SRHS), anxiety and measures of HRV and BP have been suggested, they have not been clearly established. This cross-sectional correlational study aimed to 1) examine relationships between social support, SRHS, and anxiety; and 2) examine if HRV mediated relationships between anxiety symptoms and BP. Patients with primary HTN were recruited from a cardiovascular outpatient clinic using convenience sampling (N = 300). Data included scale scores for SRHS, social support, and anxiety (Hospital Anxiety and Depression Scale). A handheld limb-lead electrocardiogram monitor measured HRV, using the ratio of low-frequency bands to high-frequency bands; an automatic sphygmomanometer measured systolic and diastolic blood pressure (SBP and DBP, respectively). Path analysis of structural equation models examined relationships between variables; the bootstrap method examined the mediating effects of HRV. Analysis showed scores for SRHS and social support had a direct effect on anxiety scores. Scores for anxiety directly affected HRV and BP. HRV also had a direct effect on BP. Bootstrapping indicated HRV mediated the relationship between anxiety symptoms and BP. The final model indicated SRHS, social support, and anxiety symptoms together explained 80% of SBP and 33% of DBP. These findings suggest HRV could be used to measure the effectiveness of strategies aimed at reducing anxiety and improving control of BP.

The effect of a single-session heart rate variability biofeedback on attentional control: does stress matter?

Introduction

Vagally mediated heart rate variability is an index of autonomic nervous system activity that is associated with a large variety of outcome variables including psychopathology and self-regulation. While practicing heart rate variability biofeedback over several weeks has been reliably associated with a number of positive outcomes, its acute effects are not well known. As the strongest association with vagally mediated heart rate variability has been found particularly within the attention-related subdomain of self-regulation, we investigated the acute effect of heart rate variability biofeedback on attentional control using the revised Attention Network Test.

Methods

Fifty-six participants were tested in two sessions. In one session each participant received a heart rate variability biofeedback intervention, and in the other session a control intervention of paced breathing at a normal ventilation rate. After the biofeedback or control intervention, participants completed the Attention Network Test using the Orienting Score as a measure of attentional control.

Results

Mixed models revealed that higher resting baseline vagally mediated heart rate variability was associated with better performance in attentional control, which suggests more efficient direction of attention to target stimuli. There was no significant main effect of the intervention on attentional control. However, an interaction effect indicated better performance in attentional control after biofeedback in individuals who reported higher current stress levels.

Discussion

The results point to acute beneficial effects of heart rate variability biofeedback on cognitive performance in highly stressed individuals. Although promising, the results need to be replicated in larger or more targeted samples in order to reach stronger conclusions about the effects.

Methods for Heart Rate Variability Biofeedback (HRVB): A Systematic Review and Guidelines

Heart Rate Variability Biofeedback (HRVB) has been widely used to improve cardiovascular health and well-being. HRVB is based on breathing at an individual's resonance frequency, which stimulates respiratory sinus arrhythmia (RSA) and the baroreflex. There is, however, no methodological consensus on how to apply HRVB, while details about the protocol used are often not well reported. Thus, the objectives of this systematic review are to describe the different HRVB protocols and detect methodological concerns. PsycINFO, CINALH, Medline and Web of Science were searched between 2000 and April 2021. Data extraction and quality assessment were based on PRISMA guidelines. A total of 143 studies were finally included from any scientific field and any type of sample. Three protocols for HRVB were found: (i) "Optimal RF" (n = 37), each participant breathes at their previously detected RF; (ii) "Individual RF" (n = 48), each participant follows a biofeedback device that shows the optimal breathing rate based on cardiovascular data in real time, and (iii) "Preset-pace RF" (n = 51), all participants breathe at the same rate rate, usually 6 breaths/minute. In addition, we found several methodological differences for applying HRVB in terms of number of weeks, duration of breathing or combination of laboratory and home sessions. Remarkably, almost 2/3 of the studies did not report enough information to replicate the HRVB protocol in terms of breathing duration, inhalation/exhalation ratio, breathing control or body position. Methodological guidelines and a checklist are proposed to enhance the methodological quality of future HRVB studies and increase the information reported.

Revisiting nonlinearity of heart rate variability in healthy aging

Aging is commonly regarded as a physiological process in which the dynamic complexity of physiological time series and organ systems is gradually lost. This notion is derived from the identification of a decline of nonlinear measures with the advance of aging. However, additional research on cardiovascular control studied through heart rate variability (HRV), i.e., the instantaneous changes in heart rate, shows that despite the constriction of its statistical distribution, the nonlinear organization remains present in advanced age. Here, we used surrogate data testing to investigate the presence of nonlinear information in HRV time series from a publicly available database of 1121 healthy human subjects from 18 to 92 years old. We also studied the influence of basic clinical features, such as sex, body mass index (BMI), and mean heart rate (HR), on such nonlinear information. We found that the percentage of nonlinear time series after 30 years of age diminishes significantly (p < 0.01). Furthermore, larger BMI and HR are associated with the presence of more linear information in HRV, while the female sex is associated with the manifestation of nonlinear information. This work provides a common background for the contextualized interpretation of nonlinear testing and shows that the nonlinear content of HRV time series diminishes through aging.

Standard Heart Rate Variability Parameters-Their Within-Session Stability, Reliability, and Sample Size Required to Detect the Minimal Clinically Important Effect

Many intervention studies assume the stability of heart rate variability (HRV) parameters, and their sample sizes are often small, which can significantly affect their conclusions. The aim of this study is to assess the stability and reliability of standard HRV parameters within a single resting session, and to estimate the sample size required to detect the minimal clinically important effect of an intervention. Heart rate was recorded in 50 adult healthy subjects for 50 min in a seated position. Eight standard HRV parameters were calculated from five evenly spaced 5 min intervals. Stability was assessed by comparing the mean values of HRV parameters between the consecutive five test-retest measurements. Absolute reliability was determined by standard error of measurement, and relative reliability by intraclass correlation coefficient. The sample size required to detect a mean difference of ≥30% of between-subject standard deviation was estimated. As expected, almost all HRV parameters had poor absolute reliability but most HRV parameters had substantial to excellent relative reliability. We found statistically significant differences in almost all HRV parameters between the first 20 min and the last 30 min of the session. The estimated sample size ranged from 19 to 300 subjects for the first 20 min and from 36 to 194 subjects for the last 30 min of the session, depending on the selected HRV parameter. We concluded that optimal HRV measurement protocols in a resting seated position should be performed within the first 20 min or between 20 and 50 min after assuming a resting seated position. Future interventional HRV studies should include a sufficient number of subjects and consider the Bonferroni correction according to the number of selected HRV parameters to achieve an appropriate level of study power and precision.

Using machine learning to estimate the calendar age based on autonomic cardiovascular function

Introduction

Aging is accompanied by physiological changes in cardiovascular regulation that can be evaluated using a variety of metrics. In this study, we employ machine learning on autonomic cardiovascular indices in order to estimate participants' age.

Methods

We analyzed a database including resting state electrocardiogram and continuous blood pressure recordings of healthy volunteers. A total of 884 data sets met the inclusion criteria. Data of 72 other participants with an BMI indicating obesity (>30 kg/m²) were withheld as an evaluation sample. For all participants, 29 different cardiovascular indices were calculated including heart rate variability, blood pressure variability, baroreflex function, pulse wave dynamics, and QT interval characteristics. Based on cardiovascular indices, sex and device, four different approaches were applied in order to estimate the calendar age of healthy subjects, i.e., relevance vector regression (RVR), Gaussian process regression (GPR), support vector regression (SVR), and linear regression (LR). To estimate age in the obese group, we drew normal-weight controls from the large sample to build a training set and a validation set that had an age distribution similar to the obesity test sample.

Results

In a five-fold cross validation scheme, we found the GPR model to be suited best to estimate calendar age, with a correlation of r=0.81 and a mean absolute error of MAE=5.6 years. In men, the error (MAE=5.4 years) seemed to be lower than that in women (MAE=6.0 years). In comparison to normal-weight subjects, GPR and SVR significantly overestimated the age of obese participants compared with controls. The highest age gap indicated advanced cardiovascular aging by 5.7 years in obese participants.

Discussion

In conclusion, machine learning can be used to estimate age on cardiovascular function in a healthy population when considering previous models of biological aging. The estimated age might serve as a comprehensive and readily interpretable marker of cardiovascular function. Whether it is a useful risk predictor should be investigated in future studies.

Heart Rate Complexity and Autonomic Modulation Are Associated with Psychological Response Inhibition in Healthy Subjects

BACKGROUND

the ability to suppress/regulate impulsive reactions has been identified as common factor underlying the performance in all executive function tasks. We analyzed the HRV signals (power of high (HF) and low (LF) frequency, Sample Entropy (SampEn), and Complexity Index (CI)) during the execution of cognitive tests to assess flexibility, inhibition abilities, and rule learning.

METHODS

we enrolled thirty-six healthy subjects, recording five minutes of resting state and two tasks of increasing complexity based on 220 visual stimuli with 12 × 12 cm red and white squares on a black background.

RESULTS

at baseline, CI was negatively correlated with age, and LF was negatively correlated with SampEn. In Task 1, the CI and LF/HF were negatively correlated with errors. In Task 2, the reaction time positively correlated with the CI and the LF/HF ratio errors. Using a binary logistic regression model, age, CI, and LF/HF ratio classified performance groups with a sensitivity and specificity of 73 and 71%, respectively.

CONCLUSIONS

this study performed an important initial exploration in defining the complex relationship between CI, sympathovagal balance, and age in regulating impulsive reactions during cognitive tests. Our approach could be applied in assessing cognitive decline, providing additional information on the brain-heart interaction.

Detecting driver fatigue using heart rate variability: A systematic review

Driver fatigue detection systems have potential to improve road safety by preventing crashes and saving lives. Conventional driver monitoring systems based on driving performance and facial features may be challenged by the application of automated driving systems. This limitation could potentially be overcome by monitoring systems based on physiological measurements. Heart rate variability (HRV) is a physiological marker of interest for detecting driver fatigue that can be measured during real life driving. This systematic review investigates the relationship between HRV measures and driver fatigue, as well as the performance of HRV based fatigue detection systems. With the applied eligibility criteria, 18 articles were identified in this review. Inconsistent results can be found within the studies that investigated differences of HRV measures between alert and fatigued drivers. For studies that developed HRV based fatigue detection systems, the detection performance showed a large variation, where the detection accuracy ranged from 44% to 100%. The inconsistency and variation of the results can be caused by differences in several key aspects in the study designs. Progress in this field is needed to determine the relationship between HRV and different fatigue causal factors and its connection to driver performance. To be deployed, HRV-based fatigue detection systems need to be thoroughly tested in real life conditions with good coverage of relevant driving scenarios and a sufficient number of participants.

Photoplethysmography (PPG)-determined heart rate variability (HRV) and extracellular water (ECW) in the evaluation of chronic stress and inflammation

BACKGROUND

Heart rate variability (HRV) is the physiological variation in the time interval between consecutive heartbeats. Extracellular water (ECW) is the aqueous compartment surrounding cells and has been used as an inflammation index. Medically unexplained symptoms (MUS) refer to persistent psychosomatic bodily complaints, and their presence may be employed as a clinical index of chronic stress and inflammation, useful in distinguishing suffering patients from healthy subjects.

AIM

To evaluate the clinical performance of SDNN (standard deviation of intracardiac beat time interval of normal sinus beats) and RMSSD (square root of the mean squared differences of successive NN intervals) as indices of HRV, and their correlation with ECW and MUS.

PATIENTS AND METHODS

A large multicenter retrospective study was conducted in 37 Italian medical practices in Caucasian men and women aged 20 to 70 years. SDNN and RMSSD were measured with the PPG Stress Flow® device (BioTekna, Italy), while ECW was determined with the BIA-ACC® device (BioTekna, Italy). All subjects filled in a MUS® questionnaire with 19 "nonspecific" symptom questions. The study sample was stratified by decade of age into five groups.

RESULTS

Data from 9246 subjects comprising 3127 males and 6119 females, with a median age of 47 years, were analyzed. HRV index SDNN and RMSSD distributions in the entire sample and in each of the five age groups were significantly greater in subjects with a limited number of MUS (0-5) than in subjects with six or more symptoms, while both distributions correlated negatively with ECW.

CONCLUSION

SDNN and RMSSD and ECW were predictors of MUS and were successfully used to objectively evaluate chronic stress and inflammation.

The Psychophysiological Profile and Cardiac Autonomic Reactivity in Long-Term Female Yoga Practitioners: A Comparison with Runners and Sedentary Individuals

Yoga practice, a means of stress management, has been reported to optimize psychophysiological health; however, its underlying mechanisms remain unclear. The purpose of the present study was to examine the psychophysiological profile and cardiac autonomic reactivity in long-term yoga practitioners and compare them to runners and sedentary individuals. Psychological health and aerobic fitness level were evaluated using self-reported questionnaires and a 3-min step test. Blood pressure (BP), heart rate (HR), respiration rate (RR), and heart rate variability (HRV) parameters were recorded at rest, as well as during and following psychological stress, which was elicited by the Stroop color and word test and the mental arithmetic task. The yoga group demonstrated a lower RR (10.35 ± 2.13 bpm) as compared to the other two groups, and a lower HR (66.60 ± 7.55 bpm) and diastolic BP (67.75 ± 8.38 mmHg) at rest when compared to the sedentary group (all p < 0.05). HRV parameters following mental stress returned to the baseline in yoga and running groups, but not in the sedentary group. The anxiety level in the running group was significantly lower than that in the sedentary group (p < 0.05). These findings suggested that yoga practitioners may have a greater homeostatic capacity and autonomic resilience than do sedentary individuals.

Inhibitory Control and Brain–Heart Interaction: An HRV-EEG Study

Background: Motor inhibition is a complex cognitive function regulated by specific brain regions and influenced by the activity of the Central Autonomic Network. We investigate the two-way Brain–Heart interaction during a Go/NoGo task. Spectral EEG ϑ, α powerbands, and HRV parameters (Complexity Index (CI), Low Frequency (LF) and High Frequency (HF) powers) were recorded. Methods: Fourteen healthy volunteers were enrolled. We used a modified version of the classical Go/NoGo task, based on Rule Shift Cards, characterized by a baseline and two different tasks of different complexity. The participants were divided into subjects with Good (GP) and Poor (PP) performances. Results: In the baseline, CI was negatively correlated with α/ϑ. In task 1, the CI was negatively correlated with the errors and α/ϑ, while the errors were positively correlated with α/ϑ. In task 2, CI was negatively correlated with the Reaction Time and positively with α, and the errors were negatively correlated with the Reaction Time and positively correlated with α/ϑ. The GP group showed, at baseline, a negative correlation between CI and α/ϑ. Conclusions: We provide a new combined Brain–Heart model underlying inhibitory control abilities. The results are consistent with the complementary role of α and ϑ oscillations in cognitive control.

Heart Rate Fractality Disruption as a Footprint of Subthreshold Depressive Symptoms in a Healthy Population

OBJECTIVE

Psychopathology (and depression in particular) is a cardiovascular risk factor independent from any co-occurring pathology. This link is traced back to the mind-heart-body connection, whose underlying mechanisms are still not completely known. To study psychopathology in relation to the heart, it is necessary to observe the autonomic nervous system, which mediates among the parts of that connection. Its gold standard of evaluation is the study of heart rate variability (HRV). To investigate whether any association exists between the HRV parameters and sub-threshold depressive symptoms in a sample of healthy subjects.

METHOD

In this cross-sectional study, two short-term HRV recordings (5 min - supine and sitting) have been analyzed in 77 healthy subjects. Here we adopted a three-fold approach to evaluate HRV: a set of scores belonging to the time domain; to the frequency domain (high, low, and very low frequencies) and a set of 'nonlinear' parameters. The PHQ-9 (Patient Health Questionnaire-9) scale was used to detect depressive symptoms.

RESULTS

Depressive symptoms were associated only with a parameter from the non-linear approach and specifically the long-term fluctuations of fractal dimensions (DFA-α2). This association remained significant even after controlling for age, gender, BMI (Body-Mass-Index), arterial hypertension, anti-hypertensive drugs, dyslipidemia, and smoking habits. Moreover, the DFA-α2 was not affected by the baroreflex (postural change), unlike other autonomic markers.

CONCLUSIONS

Fractal analysis of HRV (DFA-α2) allows then to predict depressive symptoms below the diagnostic threshold in healthy subjects regardless of their health status. DFA-α2 may be considered as an imprint of subclinical depression on the heart rhythm.

Heart rate variability in relation to cognition and behavior in neurodegenerative diseases: A systematic review and meta-analysis

Neurodegenerative diseases, which frequently present with neuropsychiatric symptoms related to prefrontal cortical dysfunction, can alter the integrity of the neural networks involved in central autonomic nervous system regulation, which is proposed to be indexed by heart rate variability (HRV). We systematically reviewed the characteristics, methodology and outcomes of 27 studies of HRV in relation to measures of cognition and behavior in neurodegenerative conditions, and assessed the strength of this relationship, cross-sectionally, across 18 studies. A significant, moderate effect was observed (r = 0.25), such that higher HRV was related to better cognitive and behavioral scores, which was not influenced by mean age or cognitive status. There was no evidence of small-study effects but we could not rule out publication bias, and other factors may have contributed to heterogeneity between studies. Our findings support the proposal that HRV may be a marker of self-regulatory processes in neurodegenerative conditions, and further research on this association is needed in relation to neuropsychiatric symptoms and alongside neuroimaging methods.

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Heart rate variability is proposed to be influenced by a neural network involved in autonomic regulation.

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Neurodegenerative processes alter the integrity of the central autonomic network.

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We reviewed studies of HRV and cognition/behavior in neurodegenerative diseases.

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We found a moderate correlation between HRV and measures of cognition/behavior.

Long- and short-term fluctuations compared for several organ systems across sleep stages

Some details of cardiovascular and cardio-respiratory regulation and their changes during different sleep stages remain still unknown. In this paper we compared the fluctuations of heart rate, pulse rate, respiration frequency, and pulse transit times as well as EEG alpha-band power on time scales from 6 to 200 s during different sleep stages in order to better understand regulatory pathways. The five considered time series were derived from ECG, photoplethysmogram, nasal air flow, and central electrode EEG measurements from full-night polysomnography recordings of 246 subjects with suspected sleep disorders. We applied detrended fluctuation analysis, distinguishing between short-term (6-16 s) and long-term (50-200 s) correlations, i.e., scaling behavior characterized by the fluctuation exponents α ₁ and α ₂ related with parasympathetic and sympathetic control, respectively. While heart rate (and pulse rate) are characterized by sex and age-dependent short-term correlations, their long-term correlations exhibit the well-known sleep stage dependence: weak long-term correlations during non-REM sleep and pronounced long-term correlations during REM sleep and wakefulness. In contrast, pulse transit times, which are believed to be mainly affected by blood pressure and arterial stiffness, do not show differences between short-term and long-term exponents. This is in constrast to previous results for blood pressure time series, where α ₁ was much larger than α ₂, and therefore questions a very close relation between pulse transit times and blood pressure values. Nevertheless, very similar sleep-stage dependent differences are observed for the long-term fluctuation exponent α ₂ in all considered signals including EEG alpha-band power. In conclusion, we found that the observed fluctuation exponents are very robust and hardly modified by body mass index, alcohol consumption, smoking, or sleep disorders. The long-term fluctuations of all observed systems seem to be modulated by patterns following sleep stages generated in the brain and thus regulated in a similar manner, while short-term regulations differ between the organ systems. Deviations from the reported dependence in any of the signals should be indicative of problems in the function of the particular organ system or its control mechanisms.

Effects of yoga and mindfulness practices on the autonomous nervous system in primary school children: A non-randomised controlled study

OBJECTIVES

The present study examined the effects of a yoga and mindfulness-based programme on the autonomic nervous system of primary school children by using heart rate variability parameters.

DESIGN

A two-arm non-randomised controlled trial compared an integrated yoga and mindfulness-based programme (16 weeks) to conventional primary school lessons.

SETTING

Primary school classrooms and conference rooms.

INTERVENTIONS

Participants were allocated to a 16-week integrated yoga-based programme or conventional school lessons. A subgroup was randomised to receive 24h electrocardiogram-recordings.

MAIN OUTCOME MEASURES

Heart rate variability indices were measured, both linear (time and frequency domain) and non-linear (symbolic dynamics, compression entropy), calculated from 30-minute extracts of Holter-electrocardiogram-recordings. Assessments were conducted at baseline and at the end of intervention.

RESULTS

40 participants (42.5% female) were included into the analysis of HRV. No significant changes in heart rate variability parameters were observed between the groups after 16 weeks. In the intervention group, a trend towards increased parasympathetic activity could be seen over time, although not significantly enhanced compared to the control group.

CONCLUSION

Results obtained here do not clearly show that children in German primary school settings benefit from an integrated yoga-based intervention. However, exploratory post-hoc analyses point interestingly to an increased nocturnal parasympathetic activity in the intervention group. Further studies are required with high-quality study designs, larger sample sizes and longer-term follow-ups.

Brief induction of loneliness decreases vagal regulation during social information processing

Perceived social isolation, or loneliness, has been repeatedly linked to numerous adverse health outcomes. Much effort has been directed towards elucidating the mechanisms underlying its effects on the cardiovascular system, which may explain the deleterious effects on morbidity and mortality. It has been previously suggested that perceived social isolation can impair effective parasympathetic regulation and physiological adjustment to the demands of the social environment. Thus, the present study aimed at investigating the causal impact of an induction of loneliness on vagal activity during social stimuli processing. In the study, participants (N = 119) were led to anticipate either a future filled with satisfying relationships (Future Belong) or a lonely life (Future Alone). Then, they were asked to complete an implicit emotion regulation task while their cardiovascular activity was recorded. In the Future Belong group, a pattern of vagal suppression was observed between the resting period and task completion, which was followed by vagal recovery during the post-task resting period. However, in the Future Alone group, a change from the baseline HRV was observed only at the beginning of the task, but not during its consecutive stages. Moreover, in participants who believed in the given FA feedback, the initial vagal suppression was absent. These findings provide evidence that even a brief induction of loneliness can result in a blunted vagal suppression during social information processing. It can be hypothesized that the lack of the ability to regulate vagal activity while processing social cues may potentially underlie problems with social engagement and self-control.

Short-Term HRV Analysis Using Nonparametric Sample Entropy for Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is associated with reduced heart rate variability (HRV) and autonomic nervous system dysfunction. Sample entropy (SampEn) is commonly used for regularity analysis. However, it has limitations in processing short-term segments of HRV signals due to the extreme dependence of its functional parameters. We used the nonparametric sample entropy (NPSampEn) as a novel index for short-term HRV analysis in the case of OSA. The manuscript included 60 6-h electrocardiogram recordings (20 healthy, 14 mild-moderate OSA, and 26 severe OSA) from the PhysioNet database. The NPSampEn value was compared with the SampEn value and frequency domain indices. The empirical results showed that NPSampEn could better differentiate the three groups (p < 0.01) than the ratio of low frequency power to high frequency power (LF/HF) and SampEn. Moreover, NPSampEn (83.3%) approached a higher OSA screening accuracy than the LF/HF (73.3%) and SampEn (68.3%). Compared with SampEn (|r| = 0.602, p < 0.05), NPSampEn (|r| = 0.756, p < 0.05) had a significantly stronger association with the apnea-hypopnea index (AHI). Hence, NPSampEn can fully overcome the influence of individual differences that are prevalent in biomedical signal processing, and might be useful in processing short-term segments of HRV signal.

Entropy Profiling: A Reduced-Parametric Measure of Kolmogorov-Sinai Entropy from Short-Term HRV Signal

Entropy profiling is a recently introduced approach that reduces parametric dependence in traditional Kolmogorov-Sinai (KS) entropy measurement algorithms. The choice of the threshold parameter r of vector distances in traditional entropy computations is crucial in deciding the accuracy of signal irregularity information retrieved by these methods. In addition to making parametric choices completely data-driven, entropy profiling generates a complete profile of entropy information as against a single entropy estimate (seen in traditional algorithms). The benefits of using "profiling" instead of "estimation" are: (a) precursory methods such as approximate and sample entropy that have had the limitation of handling short-term signals (less than 1000 samples) are now made capable of the same; (b) the entropy measure can capture complexity information from short and long-term signals without multi-scaling; and (c) this new approach facilitates enhanced information retrieval from short-term HRV signals. The novel concept of entropy profiling has greatly equipped traditional algorithms to overcome existing limitations and broaden applicability in the field of short-term signal analysis. In this work, we present a review of KS-entropy methods and their limitations in the context of short-term heart rate variability analysis and elucidate the benefits of using entropy profiling as an alternative for the same.

Early life maltreatment and resting-state heart rate variability: A systematic review and meta-analysis

Recent focus on the consequences of early life adversity (ELA) in neurobiological research led to a variety of findings suggesting alterations in several physiological systems, such as the cardiovascular system. In this systematic review and meta-analysis, we focused on the relationship between early life maltreatment (ELM), one form of ELA, and resting vagal activity indexed by resting-state heart rate variability (HRV). A systematic search of the literature yielded 1'264 hits, of which 32 studies reporting data for group comparisons or correlations were included. By quantitative synthesis of existing studies using random-effect models, we found no evidence for a relationship between ELM exposure and resting vagal activity in principal. Conducting meta-regression analyses, however, we found the relationship between ELM and resting vagal activity to significantly vary as a function of both age and the presence of psychopathology. In light of the current multitude of vastly unclear pathways linking ELM to the onset of disease, we emphasize the need for further research and outline several aspects to consider in future studies.

Herzfrequenzvariabilitätsanalyse in der betriebsärztlichen Praxis

In dem vorliegenden Beitrag werden basierend auf einer selektiven Literaturrecherche und unter Berücksichtigung aktueller Leitlinien die Rahmenbedingungen der Herzfrequenzvariabilitätsanalyse (HRV-Analyse), die Auswahl der HRV-Parameter bei den verschiedenen Fragestellungen und die Möglichkeiten der Nutzbarkeit der HRV für die betriebsärztliche Praxis zusammengefasst. Inzwischen in der praktischen Anwendung gut etabliert, werden die HRV-Parameter als Beanspruchungsindikatoren für die Einschätzung der Regulationsmechanismen und funktionalen Reserven des Herz-Kreislauf-Systems eingesetzt.

Comparisons between Manual Lymph Drainage, Abdominal Massage, and Electrical Stimulation on Functional Constipation Outcomes: A Randomized, Controlled Trial

BACKGROUND

Evidence supports abdominal massage (AM) or electrical stimulation (ES) as effective in treating functional constipation (FC). Manual lymph drainage (MLD) may also be beneficial, however, it was not previously investigated or compared to ES and AM.

METHODS

Sixteen college-aged males and 36 females were recruited. Participants were randomly assigned to MLD, AM or ES. Heart rate variability (HRV) measures for total power (TP), high frequency (HF), low frequency and LF/HF ratio assessed ANS outcomes. state-trait anxiety inventory (STAI) and stress response inventory (SRI) assessed psychological factors and bowel movement frequency (BMF) and duration (BMD) were recorded daily.

RESULTS

MLD significantly improved all ANS measures (p≤0.01); AM significantly improved LF, HF and LF/HF ratios (p = 0.04); and ES significantly improved LF (p = 0.1). STAI measures improved, but not significantly in all groups. SRI improved significantly from MLD (p < 0.01), AM (p = 0.04) and ES (p < 0.01), but changes were not significant between groups. BMD improved significantly in all groups (p≤ 0.02). BMF improved significantly only following MLD and AM (p < 0.1), but differences between groups were not significant (p = 0.39).

CONCLUSIONS

MLD significantly reduced FC symptoms and MLD had greater improvements than AM or ES.

The Trace Conditional Learning of the Noxious Stimulus in UWS Patients and Its Prognostic Value in a GSR and HRV Entropy Study

The assessment of the consciousness level of Unresponsive Wakefulness Syndrome (UWS) patients often depends on a subjective interpretation of the observed spontaneous and volitional behavior. To date, the misdiagnosis level is around 30%. The aim of this study was to observe the behavior of UWS patients, during the administration of noxious stimulation by a Trace Conditioning protocol, assessed by the Galvanic Skin Response (GSR) and Heart Rate Variability (HRV) entropy. We recruited 13 Healthy Control (HC) and 30 UWS patients at 31 ± 9 days from the acute event evaluated by Coma Recovery Scale–Revised (CRS-R) and Nociception Coma Scale (NCS). Two different stimuli [musical stimulus (MUS) and nociceptive stimulus (NOC)], preceded, respectively by two different tones, were administered following the sequences (A) MUS1 – NOC1 – MUS2 – MUS3 – NOC2 – MUS4 – NOC3 – NOC^*, and (B) MUS1^*, NOC1^*, NOC2^*, MUS2^*, NOC3^*, MUS3^*, NOC4^*, MUS4^*. All the (^*) indicate the only tones administration. CRS-R and NCS assessments were repeated for three consecutive weeks. MUS4, NOC3, and NOC^* were compared for GSR wave peak magnitude, time to reach the peak, and time of wave's decay by Wilcoxon's test to assess the Conditioned Response (CR). The Sample Entropy (SampEn) was recorded in baseline and both sequences. Machine Learning approach was used to identify a rule to discriminate the CR. The GSR magnitude of CR was higher comparing music stimulus (p < 0.0001) and CR extinction (p < 0.002) in nine patients and in HC. Patients with CR showed a higher SampEn in sequence A compared to patients without CR. Within the third and fourth weeks from protocol administration, eight of the nine patients (88.9%) evolved into MCS. The Machine-learning showed a high performance to differentiate presence/absence of CR (≥95%). The possibility to observe the CR to the noxious stimulus, by means of the GSR and SampEn, can represent a potential method to reduce the misdiagnosis in UWS patients.

First Evaluation of an Index of Low Vagally-Mediated Heart Rate Variability as a Marker of Health Risks in Human Adults: Proof of Concept

Multiple studies have demonstrated low vagally-mediated heart rate variability (HRV) being associated with a range of risk factors for heart disease and stroke, including inflammation, hyperglycemia, hyperlipidemia, and hypertension. Yet, no cut point exists that indicates elevated risk. In the present study we sought to identify a cut point-value for HRV that is associated with elevated risk across a range of known risk factors. Methods: A total of 9550 working adults from 19 study sites took part in a health assessment that included measures of inflammation, hyperglycemia, hyperlipidemia, and hypertension and vagally-mediated HRV (Root mean square of successive differences between normal heartbeats (RMSSD)). Multiple age and sex adjusted logistic regressions were calculated per risk factor (normal versus clinical range), with RMSSD being entered in binary at different cut points ranging from 15–39 msec with a 2 msec increment. Results: For daytime RMSSD, values below 25 ± 4 indicated elevated risk (odds ratios (OR) 1.5–3.5 across risk factors). For nighttime RMSSD, values below 29 ± 4 indicated elevated risk (OR 1.2–2.0). Conclusion: These results provide the first evidence that a single value of RMSSD may be associated with elevated risk across a range of established cardiovascular risk factors and may present an easy to assess novel marker of cardiovascular risk.

Heart Rate Variability and Performance of Commercial Airline Pilots during Flight Simulations

Pilots undergo a variety of stressors that may affect their performance during all phases of flight. Heart rate variability (HRV) has been considered as a reliable indicator of the parasympathetic and sympathetic activities of human autonomic nervous system, which can be used to characterize the sympathetic stress response of pilots during flight. In this study, thirty active commercial airline pilots were recruited to fly three flight segments in a Federal Aviation Administration (FAA)-certified A320 flight simulator with each segment at a different carbon dioxide (CO₂) concentration on the flight deck. The pilots performed a series of maneuvers of varying difficulty, and their performance was evaluated by FAA designated pilot examiners. The HRV metrics (SDNN, RMSSD and LF/HF ratio) of each pilot both before and during flight simulations were measured with a Movisens EcgMove3 sensor. The average SDNN, RMSSD and LF/HF ratio of the pilots during flight simulations were 34.1 ± 12.7 ms, 23.8 ± 10.2 ms and 5.7 ± 2.8 respectively. Decreased HRV was associated with aging, obesity and performing difficult maneuvers. Both CO₂ exposure and HRV had an independent effect on the pilot performance, while their interaction was not significant. The generalized additive mixed effect model results showed that a pilot performed better on a maneuver when his stress response was lower, as indicated by higher SDNN and RMSSD and lower LF/HF ratio. An interquartile range (IQR) increase in SDNN (21.97 ms) and RMSSD (16.00 ms) and an IQR decrease in LF/HF ratio (4.69) was associated with an increase in the odds of passing a maneuver by 37%, 22% and 20%, respectively.

Heart Rate Variability as an Indicator of Nociceptive Pain in Disorders of Consciousness?

CONTEXT

Heart rate variability is thought to reflect the affective and physiological aspects of pain and is emerging as a possible descriptor of the functional brain organization contributing to homeostasis.

OBJECTIVES

To investigate whether the short-term Complexity Index (CIs), a measure of heart rate variability complexity is useful to discriminate responses to potentially noxious and nonnoxious stimulation in patients with different levels of consciousness.

METHODS

Twenty-two patients (11 minimally conscious state [MCS], 11 vegetative state/unresponsive wakefulness syndrome [VS/UWS]) and 14 healthy controls (HC) were enrolled. We recorded the electrocardiographic response and calculated the CIs before (baseline), during, and after nonnoxious and noxious stimulation. Mann-Whitney and Wilcoxon's tests were used to investigate differences in CIs according to the level of consciousness (i.e., HC vs. patients and VS/UWS vs. MCS) and the three conditions (i.e., baseline, nonnoxious, noxious). The correlation between the three conditions and the Coma Recovery Scale-Revised was investigated by Spearman's correlations.

RESULTS

We observed higher CIs values in HC as compared with patients during the baseline (P < 0.034) and after the noxious stimulation (P < 0.0001). We also found higher values in MCS versus VS/UWS patients after the noxious condition (P < 0.001) and lower values in the noxious versus nonnoxious condition solely for the VS/UWS group (P < 0.007). A correlation was found between CIs in noxious condition and Coma Recovery Scale-Revised scores.

CONCLUSION

Our results suggest a less complex autonomic response to noxious stimuli in VS/UWS patients. Such method may help to better understand sympathovagal response to potentially painful stimulation in brain-injured patients.

A unified non-linear approach based on recurrence quantification analysis and approximate entropy: application to the classification of heart rate variability of age-stratified subjects

This paper presents a unified approach based on the recurrence quantification analysis (RQA) and approximate entropy (ApEn) for the classification of heart rate variability (HRV). In this paper, the optimum tolerance threshold (r_opt) corresponding to ApEn_max has been used for RQA calculation. The experimental data length (N) of RR interval series (RR_i) is optimized by taking r_opt as key parameter. r_opt is found to be lying within the recommended range of 0.1 to 0.25 times the standard deviation of the RR_i, when N ≥ 300. Consequently, RQA is applied to the age stratified RR_i and indices such as percentage recurrence (%REC), percentage laminarity (%LAM), and percentage determinism (%DET) are calculated along with ApEn_max, [Formula: see text], [Formula: see text], and an index namely the radius differential (R_D). Certain standard HRV statistical indices such as mean RR, standard deviation of RR (or NN) interval (SDNN), and the square root of the mean squared differences of successive RR intervals (RMSSD) (Eur Hear J 17:354-381, 1996) are also found for comparison. It is observed that (i) R_D can discriminate between the elderly and young subjects with a value of 0.1151 ± 0.0236 (mean ± SD) and 0.0533 ± 0.0133 (mean ± SD) respectively for the elderly and young subjects and is found to be statistically significant with p < 0.05. (ii) Similar significant discrimination was obtained using [Formula: see text] with a value of 0.1827 ± 0.0382 (mean ± SD) and 0.2248 ± 0.0320 (mean ± SD) (iii) other significant indices were found to be %REC, %DET, %LAM, SDNN, and RMSSD; however, ApEn_max was found to be insignificant with p > 0.05. The above features of RR_i time series were tested for classification using support vector machine (SVM) and multilayer perceptron neural network (MLPNN). Higher classification accuracy was achieved using SVM with a maximum value of 99.71%. Graphical abstract.

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 subjects with type 1 diabetes mellitus.

A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality. Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN). Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients.

Cardiac autonomic modulation and long-term use of amiodarone in patients with chronic Chagasic cardiopathy

BACKGROUND

Patients with chronic Chagas cardiopathy (CCC), which may be associated with cardiac arrhythmias, frequently use amiodarone, an antiarrhythmic drug that, experimentally, appears to modulate the cardiac autonomic function.

OBJECTIVE

The present cross-sectional observational study aimed to evaluate autonomic cardiac modulation in patients with CCC undergoing chronic amiodarone therapy.

METHODS

Three groups were investigated: Group 1 included patients with CCC not treated with amiodarone (n = 27); Group 2 included patients with CCC with prolonged use (at least 6 months) of amiodarone (n = 16); and Group 3 included non-Chagasic control patients (n = 23). All patients underwent a complete clinical and laboratory assessment, followed by autonomic function tests, consisting of a basal continuous electrocardiogram in the resting supine position for 10 minutes, followed by a change the orthostatic posture for a further 5 minutes. Heart rate variability (HRV) parameters (median and interquartile interval) were quantified using linear methods in the time- and frequency-domains (autoregressive spectral analysis) and nonlinear methods, including symbolic analysis.

RESULTS

Patients with CCC using amiodarone had changes in HRV suggestive of an offset in the sympatho-vagal balance with a vagal modulation predominance (normalized HF, 49.7[27.4] vs 31.1[22.8] [P < 0.05]; and percentage 2V, 40.1 [14.6] vs 21.5 [13.4] [P < 0.05] vs untreated CCC group). These changes were further accompanied by increases in parameters indicative of greater complexity of HRV.

CONCLUSIONS

The deviation in the sympatho-vagal balance and the increase in the complexity of HRV strongly suggest that amiodarone may have a cardioprotective effect, in addition to its antiarrhythmic effects, which could increase the survival of these patients.

Nonlinear analyses of heart rate variability in hypertension

OBJECTIVE

The autonomic nervous system plays an important role in blood pressure regulation and in the development of hypertension. Heart rate variability (HRV) may be of importance in identifying subjects at higher risk of developing hypertension. In the present study, comparative analysis of HRV for normal and hypertension subjects using nonlinear indices has been carried out.

PATIENTS AND METHODS

We analyzed the data from 24 patients with essential hypertension aged 45-55 (HG). All the subjects in this group had a confirmed diagnosis of the first- or second-stage essential hypertension. The control group for these subjects included 32 healthy volunteers of the same age group (CG). We analyzed the whole 5minutes of the ECG recording. Nonlinear indices D₂, K₂ and lagged Poincaré plot indices were calculated.

RESULTS

Values of D₂ and K₂ in hypertension state is statistically significantly lower than in healthy. Poincaré plot indices SD1 and SD2 in healthy volunteers are statistically higher than in hypertensive patients for all lags (P<0,05). SD1/SD2 ratio is also higher in healthy subjects, but the difference is statistically significant only for l=5 and 6.

CONCLUSION

The heart rhythm in groups with hypertension is more regular, its dynamics are less complex and less "chaotic," compared to healthy ones. This is expressed in lower values of entropy and correlation dimension. The HR stabilization is observed at both short and long time intervals, but mainly due to the decrease in the difference of the "neighboring" R-R intervals.

Bidirectional Cardio-Respiratory Interactions in Heart Failure

We investigated cardio-respiratory coupling in patients with heart failure by quantification of bidirectional interactions between cardiac (RR intervals) and respiratory signals with complementary measures of time series analysis. Heart failure patients were divided into three groups of twenty, age and gender matched, subjects: with sinus rhythm (HF-Sin), with sinus rhythm and ventricular extrasystoles (HF-VES), and with permanent atrial fibrillation (HF-AF). We included patients with indication for implantation of implantable cardioverter defibrillator or cardiac resynchronization therapy device. ECG and respiratory signals were simultaneously acquired during 20 min in supine position at spontaneous breathing frequency in 20 healthy control subjects and in patients before device implantation. We used coherence, Granger causality and cross-sample entropy analysis as complementary measures of bidirectional interactions between RR intervals and respiratory rhythm. In heart failure patients with arrhythmias (HF-VES and HF-AF) there is no coherence between signals (p < 0.01), while in HF-Sin it is reduced (p < 0.05), compared with control subjects. In all heart failure groups causality between signals is diminished, but with significantly stronger causality of RR signal in respiratory signal in HF-VES. Cross-sample entropy analysis revealed the strongest synchrony between respiratory and RR signal in HF-VES group. Beside respiratory sinus arrhythmia there is another type of cardio-respiratory interaction based on the synchrony between cardiac and respiratory rhythm. Both of them are altered in heart failure patients. Respiratory sinus arrhythmia is reduced in HF-Sin patients and vanished in heart failure patients with arrhythmias. Contrary, in HF-Sin and HF-VES groups, synchrony increased, probably as consequence of some dominant neural compensatory mechanisms. The coupling of cardiac and respiratory rhythm in heart failure patients varies depending on the presence of atrial/ventricular arrhythmias and it could be revealed by complementary methods of time series analysis.

Smart detection of atrial fibrillation†

Aims

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, and its paroxysmal nature makes its detection challenging. In this trial, we evaluated a novel App for its accuracy to differentiate between patients in AF and patients in sinus rhythm (SR) using the plethysmographic sensor of an iPhone 4S and the integrated LED only.

Methods and results

For signal acquisition, we used an iPhone 4S, positioned with the camera lens and LED light on the index fingertip. A 5 min video file was recorded with the pulse wave extracted from the green light spectrum of the signal. RR intervals were automatically identified. For discrimination between AF and SR, we tested three different statistical methods. Normalized root mean square of successive difference of RR intervals (nRMSSD), Shannon entropy (ShE), and SD1/SD2 index extracted from a Poincaré plot. Eighty patients were included in the study (40 patients in AF and 40 patients in SR at the time of examination). For discrimination between AF and SR, ShE yielded the highest sensitivity and specificity with 85 and 95%, respectively. Applying a tachogram filter resulted in an improved sensitivity of 87.5%, when combining ShE and nRMSSD, while specificity remained stable at 95%. A combination of SD1/SD2 index and nRMSSD led to further improvement and resulted in a sensitivity and specificity of 95%.

Conclusion

The algorithm tested reliably discriminated between SR and AF based on pulse wave signals from a smartphone camera only. Implementation of this algorithm into a smartwatch is the next logical step.

Understanding Irregularity Characteristics of Short-Term HRV Signals Using Sample Entropy Profile

Sample entropy (), a popularly used "regularity analysis" tool, has restrictions in handling short-term segments (largely ) of heart rate variability (HRV) data. For such short signals, the estimate either remains undefined or fails to retrieve "accurate" regularity information. These limitations arise due to the extreme dependence of on its functional parameters, in particular the tolerance . Evaluating at a single random choice of parameter is a major cause of concern in being able to extract reliable and complete regularity information from a given signal. Here, we hypothesize that, finding a complete profile of (in contrast to a single estimate) corresponding to a data specific set of values may facilitate enhanced information retrieval from short-term signals. We introduce a novel and computationally efficient concept of profiling in order to eliminate existing inaccuracies seen in the case of estimation. Using three different HRV datasets from the PhysioNet database-first, real and simulated, second, elderly and young, and third, healthy and arrhythmic; we demonstrate better definiteness and classification performance of profile based estimates ( and ) when compared to conventional and estimates. Our novelty is to identify the importance of reliability in short-term signal regularity analysis, and our proposed approach aims to enhance both quality and quantity of information from any short-term signal.

Relationship between diabetes mellitus and heart rate variability in community-dwelling elders

BACKGROUND AND OBJECTIVE

Diabetes mellitus is one of the most common non-communicable diseases (NCDs) and may influence the autonomic nervous system. This study aims to analyze the autonomic control, through heart rate variability (HRV), from community-dwelling elders with (DM+) and without diabetes mellitus (DM-).

MATERIALS AND METHODS

This cross-sectional study, in which 205 elders (≥ 60 years old), from the urban area of Aiquara municipality gave their written consent to participate. HRV data was collected through a Polar RS800CX monitor with a 5-min initial record at rest, followed by the command to quickly stand up.

RESULTS

The mean age was 71 years (SD, 7.32). The population was mostly made up of women 121 (59%), with low or no schooling 123 (60%), and low income 166 (81%). HRV analysis in a frequency domain showed no difference when comparing the two groups of DM+ and DM-. Henceforth in a time domain, the rMSSD showed a median value of 16.09 (interquartile range, 9.91-30.68); pNN50 median of 0.79 (interquartile range, 0.00-6.62), with a statistical significance between the group of DM+ and DM-.

CONCLUSIONS

There is a difference between the studied groups principally in what concerns the time domain, which reflects the parasympathetic activity, suggesting that elders with diabetes mellitus may have a worse parasympathetic control.

Informative Nature and Nonlinearity of Lagged Poincaré Plots Indices in Analysis of Heart Rate Variability

Lagged Poincaré plots have been successful in characterizing abnormal cardiac function. However, the current research practices do not favour any specific lag of Poincaré plots, thus complicating the comparison of results of different researchers in their analysis of heart rate of healthy subjects and patients. We researched the informative nature of lagged Poincaré plots in different states of the autonomic nervous system. It was tested in three models: different age groups, groups with different balance of autonomous regulation, and in hypertensive patients. Correlation analysis shows that for lag l = 6, SD1/SD2 has weak (r = 0.33) correlation with linear parameters of heart rate variability (HRV). For l more than 6 it displays even less correlation with linear parameters, but the changes in SD1/SD2 become statistically insignificant. Secondly, surrogate data tests show that the real SD1/SD2 is statistically different from its surrogate value and the conclusion could be made that the heart rhythm has nonlinear properties. Thirdly, the three models showed that for different functional states of the autonomic nervous system (ANS), SD1/SD2 ratio varied only for lags l = 5 and 6. All of this allow to us to give cautious recommendation to use SD1/SD2 with lags 5 and 6 as a nonlinear characteristic of HRV. The received data could be used as the basis for continuing the research in standardisation of nonlinear analytic methods.

Autonomic dysfunction in primary Sjogren's syndrome: a prospective cohort analysis of 154 Korean patients

BACKGROUND/AIMS

To determine the prevalence of autonomic dysfunction among Korean patients with primary Sjogren's syndrome (pSS) and its associations with the clinical features of pSS.

METHODS

We analyzed 154 participants from the Korean Initiative of primary Sjogren's Syndrome (KISS) as a prospective pSS cohort and 154 age- and sex-matched healthy controls. A standardized 5-minute, supine, resting heart rate variability (HRV) test was performed, and autonomic dysfunction was defined as standard deviation of normal-to-normal RR intervals (SDNN) < 30 ms in patients < 50 years old and SDNN < 20 ms in patients ≥ 50 years old. The associations between autonomic dysfunction and various clinical features of pSS were analyzed.

RESULTS

The overall autonomic activity in patients with pSS was significantly lower than that in controls. Autonomic dysfunction with the HRV test was observed in 35.7% of the KISS participants and was associated with a higher European League Against Rheumatism Sjogren's Syndrome Patient Reported Index fatigue score (p = 0.024). Raynaud's phenomenon was a more frequent clinical presentation in pSS patients with autonomic dysfunction than in those without autonomic dysfunction (29.4% and 14.4%, respectively; p = 0.048). Decreased parasympathetic activity was observed in 41.6% of pSS patients. No differences were found in the oral and ocular signs of pSS according to the decreased parasympathetic activity.

CONCLUSIONS

In Korean patients with pSS, decreased and imbalanced autonomic activity is prevalent and is associated with fatigue. However, an association between autonomic dysfunction and glandular manifestations was not detected.

Aging and cardiovascular complexity: effect of the length of RR tachograms

As we age, our hearts undergo changes that result in a reduction in complexity of physiological interactions between different control mechanisms. This results in a potential risk of cardiovascular diseases which are the number one cause of death globally. Since cardiac signals are nonstationary and nonlinear in nature, complexity measures are better suited to handle such data. In this study, three complexity measures are used, namely Lempel-Ziv complexity (LZ), Sample Entropy (SampEn) and Effort-To-Compress (ETC). We determined the minimum length of RR tachogram required for characterizing complexity of healthy young and healthy old hearts. All the three measures indicated significantly lower complexity values for older subjects than younger ones. However, the minimum length of heart-beat interval data needed differs for the three measures, with LZ and ETC needing as low as 10 samples, whereas SampEn requires at least 80 samples. Our study indicates that complexity measures such as LZ and ETC are good candidates for the analysis of cardiovascular dynamics since they are able to work with very short RR tachograms.

Loss of Breathing Modulation of Heart Rate Variability in Patients with Recent and Long Standing Diabetes Mellitus Type II

Healthy subjects under rhythmic breathing have heart interbeat intervals with a respiratory band in the frequency domain that can be an index of vagal activity. Diabetes Mellitus Type II (DM) affects the autonomic nervous system of patients, thus it can be expected changes on the vagal activity. Here, the influence of DM on the breathing modulation of the heart rate is evaluated by analyzing in the frequency domain heart interbeat interval (IBI) records obtained from 30 recently diagnosed, 15 long standing DM patients, and 30 control subjects during standardized clinical tests of controlled breathing at 0.1 Hz, supine rest and standing upright. Fourier spectral analysis of IBI records quantifies heart rate variability in different regions: low-frequencies (LF, 0.04–0.15 Hz), high-frequencies (HF, 0.15–0.4 Hz), and a controlled breathing peak (RP, centered around 0.1 Hz). Two new parameters are introduced: the frequency radius r_f (square root of the sum of LF and HF squared) and β (power of RP divided by the sum of LF and HF). As diabetes evolves, the controlled breathing peak loses power and shifts to smaller frequencies, indicating that heart rate modulation is slower in diabetic patients than in controls. In contrast to the traditional parameters LF, HF and LF/HF, which do not show significant differences between the three populations in neither of the clinical tests, the new parameters r_f and β, distinguish between control and diabetic subjects in the case of controlled breathing. Sympathetic activity that is driven by the baroreceptor reflex associated with the 0.1 Hz breathing modulations is affected in DM patients. Diabetes produces not only a rigid heartbeat with less autonomic induced variability (r_f diminishes), but also alters the coupling between breathing and heart rate (reduced β), due to a progressive decline of vagal and sympathetic activity.

Symbolic dynamics of heart rate variability — a promising tool to investigate cardiac sympathovagal control in attention deficit/hyperactivity disorder (ADHD)?

We aimed to evaluate complex cardiac sympathovagal control in attention deficit/hyperactivity disorder (ADHD) by using heart rate variability (HRV) nonlinear analysis — symbolic dynamics. We examined 29 boys with untreated ADHD and 25 healthy boys (age 8–13 years). ADHD symptoms were evaluated by ADHD-RS-IV scale. ECG was recorded in 3 positions: baseline supine position, orthostasis, and clinostasis. Symbolic dynamics indices were used for the assessment of complex cardiac sympathovagal regulation: normalised complexity index (NCI), normalised unpredictability index (NUPI), and pattern classification measures (0V%, 1V%, 2LV%, 2UV%). The results showed that HRV complexity was significantly reduced at rest (NUPI) and during standing position (NCI, NUPI) in ADHD group compared to controls. Cardiac-linked sympathetic index 0V% was significantly higher during all posture positions and cardiovagal index 2LV% was significantly lower to standing in boys suffering from ADHD. Importantly, ADHD symptom inattention positively correlated with 0V%, and negatively correlated with NCI, NUPI. Concluding, symbolic dynamics revealed impaired complex neurocardiac control characterised by potential cardiac beta-adrenergic overactivity and vagal deficiency at rest and to posture changes in boys suffering from ADHD that is correlated with inattention. We suggest that symbolic dynamics indices could represent promising cardiac biomarkers in ADHD.

Guidelines for Reporting Articles on Psychiatry and Heart rate variability (GRAPH): recommendations to advance research communication

The number of publications investigating heart rate variability (HRV) in psychiatry and the behavioral sciences has increased markedly in the last decade. In addition to the significant debates surrounding ideal methods to collect and interpret measures of HRV, standardized reporting of methodology in this field is lacking. Commonly cited recommendations were designed well before recent calls to improve research communication and reproducibility across disciplines. In an effort to standardize reporting, we propose the Guidelines for Reporting Articles on Psychiatry and Heart rate variability (GRAPH), a checklist with four domains: participant selection, interbeat interval collection, data preparation and HRV calculation. This paper provides an overview of these four domains and why their standardized reporting is necessary to suitably evaluate HRV research in psychiatry and related disciplines. Adherence to these communication guidelines will help expedite the translation of HRV research into a potential psychiatric biomarker by improving interpretation, reproducibility and future meta-analyses.

Visualization of multivariate physiological data for cardiorespiratory fitness assessment through ECG (R-peak) analysis

The recent rise and popularization of wearable and ubiquitous fitness sensors has increased our ability to generate large amounts of multivariate data for cardiorespiratory fitness (CRF) assessment. Consequently, there is a need to find new methods to visualize and interpret CRF data without overwhelming users. Current visualizations of CRF data are mainly tabular or in the form of stacked univariate plots. Moreover, normative data differs significantly between gender, age and activity, making data interpretation yet more challenging. Here we present a CRF assessment tool based on radar plots that provides a way to represent multivariate cardiorespiratory data from electrocardiographic (ECG) signals within its normative context. To that end, 5 parameters are extracted from raw ECG data using R-peak information: mean HR, SDNN, RMSSD, HRVI and the maximal oxygen uptake, VO2max. Our tool processes ECG data and produces a visualization of the data in a way that it is easy to compare between the performance of the user and normative data. This type of representation can assist both health professionals and non-expert users in the interpretation of CRF data.

Temporal analysis of cardiac autonomic regulation during orthostatic challenge by short-term symbolic dynamics

The gradual shift of cardiac autonomic regulation toward sympathetic predominance and vagal withdrawal during graded head-up tilt test in young controls has been demonstrated by parameters from symbolic dynamics obtained from short-term heart rate variability (HRV) analysis. In this study, the influence of gender and vasovagal syncope (VVS) on the autonomic response to an orthostatic challenge was investigated by HRV analysis using short-term symbolic dynamics (STSD). This study included 24 healthy young subjects (12 males; 12 age-matched females) and 16 female patients diagnosed with VVS. All subjects were enrolled in a head-up tilt (HUT) test, breathing normally, including 5 minutes of supine position (baseline) and 20-40 minutes of 70° orthostatic phase. The STSD parameters were obtained following their behavior at different times during the HUT test, i.e., at baseline, early and middle orthostatic phases. Gender differences including increased sympathetic activity in men were already present in baseline and in the middle tilt phase. In baseline there were no differences between female controls and female patients, but parameters from STSD showed highly significantly (p=0.0007) reduced heart rate variability due to increased sympathetic activity in female patients in the middle tilt phase. Furthermore a new nonlinear index for the estimation of sympatho-vagal balance was introduced.

Integrating affective and cognitive correlates of heart rate variability: A structural equation modeling approach

High frequency heart rate variability (HRV) is a measure of neurocardiac communication thought to reflect predominantly parasympathetic cardiac regulation. Low HRV has been associated empirically with clinical and subclinical levels of anxiety and depression and, more recently, high levels of HRV have been associated with better performance on some measures of executive functioning (EF). These findings have offered support for theories proposing HRV as an index measure of a broad, self-regulatory capacity underlying aspects of emotion regulation and executive control. This study sought to test that proposition by using a structural equation modeling approach to examine the relationships of HRV to negative affect (NA) and EF in a large sample of U.S. adults ages 30s-80s. HRV was modeled as a predictor of an NA factor (self-reported trait anxiety and depression symptoms) and an EF factor (performance on three neuropsychological tests tapping facets of executive abilities). Alternative models also were tested to determine the utility of HRV for predicting NA and EF, with and without statistical control of demographic and health-related covariates. In the initial structural model, HRV showed a significant positive relationship to EF and a nonsignificant relationship to NA. In a covariate-adjusted model, HRV's associations with both constructs were nonsignificant. Age emerged as the only significant predictor of NA and EF in the final model, showing inverse relationships to both. Findings may reflect population and methodological differences from prior research; they also suggest refinements to the interpretations of earlier findings and theoretical claims regarding HRV.

Influence of age and gender on complexity measures for short term heart rate variability analysis in healthy subjects

Short-term heart rate variability (HRV) analyses (less than 30 min) are suitable for ambulatory care and patient monitoring and can provide an almost immediate test result. Short-term 5 min HRV indices from nonlinear dynamics were determined from 782 females and 1124 males from the KORA S4 database. We applied various fractal and complexity measures with focus on entropies and investigated the influence of age in terms of five age decades (25-34, 35-44, 45-54, 55-64 and 65-74 years) and gender on these HRV indices. The analyses revealed significant modifications of the indices especially by age but partly also by gender especially in the younger groups. These results should be considered in future studies applying nonlinear dynamics, especially if major age and gender differences between the investigated groups are expected.