Heart rate variability: origins, methods, and interpretive caveats.

The analysis and interpretation of heart rate variability (HRV) during exercise is challenging not only because of the nonstationary nature of exercise, the time-varying mean heart rate, and the fact that respiratory frequency exceeds 0.4 Hz, but there are also other factors, such as the component centered at the pedaling frequency observed in maximal cycling tests, which may confuse the interpretation of HRV analysis. The objectives of this study are to test the hypothesis that a component centered at the running stride frequency (SF) appears in the HRV of subjects during maximal treadmill exercise testing, and to study its influence in the interpretation of the low-frequency (LF) and high-frequency (HF) components of HRV during exercise. The HRV of 23 subjects during maximal treadmill exercise testing is analyzed. The instantaneous power of different HRV components is computed from the smoothed pseudo-Wigner-Ville distribution of the modulating signal assumed to carry information from the autonomic nervous system, which is estimated based on the time-varying integral pulse frequency modulation model. Besides the LF and HF components, the appearance is revealed of a component centered at the running SF as well as its aliases. The power associated with the SF component and its aliases represents 22±7% (median±median absolute deviation) of the total HRV power in all the subjects. Normalized LF power decreases as the exercise intensity increases, while normalized HF power increases. The power associated with the SF does not change significantly with exercise intensity. Consideration of the running SF component and its aliases is very important in HRV analysis since stride frequency aliases may overlap with LF and HF components.

Reports on autonomic responses to transcutaneous auricular vagus nerve stimulation (taVNS) and osteopathic manipulative techniques have been equivocal, partly due to inconsistent interpretation of heart rate variability (HRV). We developed a mechanistic framework for the interpretation of HRV based on a model of sinus node automaticity that considers autonomic effects on Phase 3 repolarization and Phase 4 depolarization of the sinoatrial action potential. The model was applied to HRV parameters calculated from ECG recordings (healthy adult humans, both genders) before (30 min), during (15 min), and after (30 min) a time control intervention (rest, n = 23), taVNS (10 Hz, 300 μs, 1–2 mA, cymba concha, left ear, n = 12), or occipitoatlantal decompression (OA‐D, n = 14). The experimental protocol was repeated on 3 consecutive days. The model simulation revealed that low frequency (LF) HRV best predicts sympathetic tone when calculated from heart rate time series, while high frequency (HF) HRV best predicts parasympathetic tone when calculated from heart period time series. Applying our model to the HRV responses to taVNS and OA‐D, revealed that taVNS increases cardiac parasympathetic tone, while OA‐D elicits a mild decrease in cardiac sympathetic tone.

Changes in the function of the autonomic nervous system underlying changes in heart rate variability are not fully understood. Furthermore, decreased heart rate variability has been found to be related to poor prognosis, for example, in patients with coronary artery disease. Our aim was to study how modulation in sympathetic stimulation at various frequencies is transferred into heart rate variation, and how the interaction between sympathetic and parasympathetic inputs can affect the high-frequency component of heart rate variability. We stimulated electrically cardiac sympathetic and vagal nerves in anaesthetized, vagotomized, spinal anaesthetized dogs. We controlled the frequency and magnitude of the modulation in programmed stimulation patterns and analysed the resulting changes in heart rate variability by power spectral analysis. We found that modulations in sympathetic stimulation were reflected in the high-frequency component of heart rate variability, as well as in the low- and medium-frequency components. In addition, a novel finding was that sympathetic stimulation reduced the magnitude of the high-frequency variations caused by vagal stimulation. This suggests that, although the high-frequency component of heart rate variability is mainly under parasympathetic regulation, it may also be influenced by the sympathetic nervous system.

Purpose: Heart rate variability (HRV) has been used for decades as a tool for measuring systemic health through the autonomic nervous system (ANS). The purpose of this paper was to examine the literature on HRV and to investigate its use in the long COVID (LC) population. Summary of Key Points: Measurement devices vary significantly in their validity and reliability when compared with the gold standard of electrocardiogram (ECG). Wrist and hand devices typically demonstrate diminished validity for capturing HRV signal, while chest strap devices often exhibit high reliability and validity. Lack of transparency in third-party software used to clean and analyze HRV data makes assessment for accuracy problematic. This is of particular concern when single beat miscalculations can result in significantly dissimilar output. The conditions under which HRV data are collected, such as natural or paced breathing, activity intensity, and patient position, can dramatically affect HRV readings. While some individual HRV metrics have consistently been shown to reflect certain components of the ANS, such as high-frequency power as a measure of parasympathetic function, the meaning of other metrics is less clear. Recommendations for Clinical Practice: Heart rate variability can be an extraordinarily valuable tool to measure systemic function. However, it is recommended that clinicians be judicious in the interpretation of HRV, considering inconsistencies in presentation. This is particularly true in LC, where individual HRV varies greatly. In all populations, clinicians should consider using valid devices to assess trends in HRV values over time, along with consideration of unique physical conditions.

In order to investigate the response of heart rate variability (HRV) components to postural change and their association with cardiovascular risk factors in shift workers, a cross-sectional study with 438 Brazilian males rotating shift workers was done. Anthropometric, body composition, and clinical measures were collected. Electrocardiogram was recorded for 3 minutes, in the supine and orthostatic position, and HRV components were extracted. Descriptive analyses showed that mean values of body mass index, waist circumference (WC), waist-to-height ratio, visceral fat area (VFA), and blood pressure (BP) were higher than the reference values. In the regression model, age, WC, VFA, and systolic BP showed negative association with HRV components. These findings suggest the need for determining effective strategies for the evaluation and promotion of health among shift workers focused on the altered variables.

Contribution of the renin-angiotensin and kallikrein-kinin systems to short-term variability of blood pressure in two-kidney, one-clip hypertensive rats

We investigated whether the 0.1-Hz component of heart rate variability (HRV) allows one to discriminate among levels of mental work stress induced by different types of tasks (diagnosticity) as well as among those induced by different levels of difficulty (sensitivity). Our 14 participants were presented 14 tasks of the Advisory Group for Aerospace Research and Development Standardized Tests for Research with Environmental Stressors battery in a repeated-measures design. Sufficient sensitivity was obtained for a discrimination between work and rest, but we found no support for a more fine-grained sensitivity. Concerning diagnosticity, only the grammatical reasoning task could be discriminated from all other tasks, indicating for this task a level of mental strain comparable to rest, which was in contrast with the results both for perceived difficulty and performance. We propose that HRV is an indicator for time pressure or emotional strain, not for mental workload, given that it seems to allow discrimination between tasks with and without pacing. Application of this research argues against using HRV as a measure of mental and especially cognitive workload, particularly where system safety or occupational risks may be at stake (e.g., when evaluating operator tasks or interface design in control room operations).

It has been shown that heart rate variability is decreased in patients with congestive heart failure and that depressed heart rate variability is associated with a propensity to ventricular arrhythmias. Little is known, however, about heart rate variability in patients with both congestive heart failure and ventricular arrhythmias. Spectral heart rate variability was analysed from 24 hour ambulatory electrocardiograms in 15 controls, 15 patients with non-sustained ventricular tachycardia associated with clinically normal hearts (NHVT group), and 40 patients with congestive heart failure (CHF group) secondary to either ischaemic heart disease (n = 15) or idiopathic dilated cardiomyopathy (n = 25). Of the 40 patients with congestive heart failure 15 had no appreciable ventricular arrhythmias (ventricular extrasystoles < 10 beats/h and no salvos) and formed the CHF-VA- group. Another 15 patients with congestive heart failure and non-sustained ventricular tachycardia formed the CHF-NSVT group. Heart rate variability was significantly lower in the CHF group than in controls (mean (SD) total frequency 23 (12) v 43 (13) ms; low frequency 12 (8) v 28 (9) ms; high frequency 8 (5) v 14 (7) ms; p < 0.001). The differences in heart rate variability between controls and the NHVT group, between ischaemic heart disease and dilated cardiomyopathy, and between the CHF-VA- and CHF-NSVT groups were not significant. In the CHF group heart rate variability was significantly related to left ventricular ejection fraction but not associated with ventricular arrhythmias. The frequency of ventricular extrasystoles was significantly related to the high frequency component of heart rate variability (r = 0.54, p < 0.05) in the NHVT group. Stepwise multiple regression analysis showed that in the CHF group, heart rate variability was predominantly related to left ventricular ejection fraction (p < 0.05). There was no significant difference in heart rate variability between survivors (n = 34) and those who died suddenly (n = 6) at one year of follow up in the CHF group. In patients with congestive heart failure, heart rate variability is significantly decreased. The depressed heart rate variability is principally related to the degree of left ventricular impairment and is independent of aetiology and the presence of ventricular arrhythmias. The data suggest that analysis of heart rate variability does not help the identification of patients with congestive heart failure at increased risk of sudden death.

Air pollution and heart rate variability among the elderly in Mexico City.

Cardiovascular reflexes during anesthesia induction and tracheal intubation in elderly patients: The influence of thoracic epidural anesthesia

Changes in heart rate variability in sevoflurane and nitrous oxide anesthesia: effects of respiration and depth of anesthesia

Analysis of any effect of retrobulbar block during ocular surgery on heart rate variability and oculocardiac reflex. Prospective study. Horses (n = 16) undergoing eye enucleation due to chronic ophthalmologic diseases. Eye enucleation was performed under general anesthesia. The horses were randomly assigned to the first (inhalation anesthesia only, n = 10) or second group (inhalation and local retrobulbar anesthesia, n = 6). The retrobulbar block was performed using 12 mL of mepivacaine hydrochloride 2%. ECG data were taken by a Telemetric ECG before, during, and after surgery. Heart rate variability was analyzed in the time domain as mean heart rate, mean beat-to-beat interval duration, and standard deviation of continuous beat-to-beat intervals. The frequency domain analysis included the low- and high-frequency components of heart rate variability and the sympathovagal balance (low/high frequency). The low frequency represents mainly sympathetic influences on the heart, whereas high frequency is mediated by the parasympathetic tone. All horses without a retrobulbar block showed a significant decrease in the heart rate during traction on the globe and pressure on the orbital fat pad for homoestasis (P = 0.04). Simultaneously, high-frequency power, as an indicator of vagal stimulation, increased significantly. High-frequency and low-frequency power in the retrobulbar block group increased in five horses, and heart rate decreased in only one horse. Both were not significant within the group, but there was a significant difference between both groups relating to the incidence of heart rate decrease occurring at globe traction. Heart rate variability is a sensitive, non-invasive parameter to obtain sympathovagal stimulations during general anesthesia. The retrobulbar block can prevent heart rate decrease associated with initiation of the oculocardiac reflex.

ObjectiveThe association between panic disorder (PD) and heart rate variability (HRV) has long been studied with a focus on the imbalance of the autonomic nervous system. This study aims to demonstrate the predictive capability of HRV in determining PD severity using machine learning.MethodsPsychometric scales and various HRV components were measured from 507 PD patients who were recruited. We designed three experiments with different sets of input features for comparison. The input features of each experiment were 1) both psychometric scales and HRV together (ExSH), or 2) only the scales (ExS), or 3) only the HRV components. In each experiment, nine machine learning models were used to predict the Panic Disorder Severity Scale. We compared the predictive capability of the three sets of input features by statistically analyzing the performance metrics of the models in the three experiments. SHapley Additive exPlanation (SHAP) was further employed to assess the importance of the input features.ResultsThe Random Forest model in ExSH, which incorporated both psychometric scales and HRV, achieved the highest f1-score (76.50%) and sensitivity (75.35%). ExSH showed significantly higher sensitivity and f1-score compared to ExS. For the RF model of ExSH, the highest SHAP importance value was found for the Hamilton Rating Scale for Anxiety, followed by the Hamilton Depression Rating Scale, and the low-frequency power (LF).ConclusionOur findings demonstrate that integrating HRV with psychometric scales improves machine learning-based prediction of PD severity. We also highlighted LF as a promising variable among HRV components.

Day-to-day variability of the long-term fractal component of heart rate variability (β) and the effect of an antianginal agent in patients with silent myocardial ischemia

Background: The integrity of the autonomic nervous system (ANS) is essential for keeping physiological processes stable, even under stress. Since there is growing interest in heart rate variability (HRV) analysis for the noninvasive assessment of the ANS in sickle cell anemia (SCA) patients, we studied the behavior of the ANS in the presence of a stressor that simulates daily-life multitasking, the Glittre ADL test (GA-T). Objectives: To evaluate the involvement of the ANS using HRV in adults with SCA during the GA-T and to quantify the strength of the correlation of HRV with lung and muscle functions. Methods: In this cross-sectional study, 16 adults with SCA and 12 healthy controls without sickle cell disease underwent HRV assessment during the GA-T, pulmonary function tests (spirometry, diffusing capacity for carbon monoxide (DLCO), and respiratory muscle testing). Peripheral muscle function [handgrip strength (HGS) and quadriceps strength (QS)] were also measured. Results: Compared to the healthy controls, adults with SCA showed lower HRV, with worse parasympathetic modulation due to reductions in the following indices: the root-mean-square difference of successive normal iRRs (iRR) (RMSSD); the percentage of pairs of consecutive iRRs whose difference is &gt; 50 m (pNN50); the high-frequency component of heart rate variability (HF); and the standard deviation of instantaneous beat-to-beat variability (SD1) (P &lt; 0.001 for all). Compared to healthy controls, individuals with SCA showed greater sympathovagal imbalance (higher ratio between low-frequency and HF components) and lower complexity of the ANS (lower approximate entropy). The GA-T time was correlated with parasympathetic activity indices: RMSSD (rs = -0.650, P &lt; 0.01); pNN50 (rs = -0.932, P &lt; 0.0001), HF (rs = -0.579, P &lt; 0.01), and SD1 (rs = -0.814, P &lt; 0.0001). Correlations between parasympathetic activity indices and DLCO, HGS, and QS measures were also significant. Conclusions: Adults with SCA have low HRV, with low parasympathetic activity, sympathovagal imbalance, and abnormal ANS complexity. In addition, lower HRV is associated with longer GA-T time, greater impairment of pulmonary diffusion, and greater muscle strength dysfunction.