Reliability and accuracy of heart rate variability metrics versus ECG segment duration

Vagus nerve stimulation and heart rate variability: A scoping review of a somatic oscillatory signal

The goal of this review is to synthesize the literature on vagus nerve stimulator (VNS)-related changes in heart rate variability (HRV) in patients with drug-resistant epilepsy (DRE) and assess the role of these changes in seizure relief. A scoping literature review was performed with the following inclusion criteria: primary articles written in English, involved implantable VNS in humans, and had HRV as a primary outcome. Twenty-nine studies were retrieved, however with considerable heterogeneity in study methods. The overall depression in HRV seen in DRE patients compared to healthy controls persisted even after VNS implant, indicating that achieving "healthy" HRV is not necessary for VNS therapeutic success. Within DRE patients, changes in frequency domain parameters six months after VNS implant returned to baseline after a year. The mechanism of how VNS reduces seizure burden does not appear to be significantly related to alterations in baseline HRV. However, the subtlety of sympathetic/parasympathetic signaling likely requires a more structured approach to experimental and analytic techniques than currently found in the literature.

Baseline heart rate variability predicts placebo hypoalgesia in men, but not women

Introduction

Placebo hypoalgesic effects vary greatly across individuals, making them challenging to control for in clinical trials and difficult to use in treatment. We investigated the potential of resting vagally-mediated heart rate variability (vmHRV) to help predict the magnitude of placebo responsiveness.

Methods

In two independent studies (total N = 77), we administered a placebo paradigm after measuring baseline HRV. In Study I, we delivered heat pain to the forearm, on skin patches treated with "real" and "control" cream (identical inactive creams). In Study II, electrical pulses to the forearm were modulated by sham transcutaneous electrical nerve stimulation. We combined data from both studies to evaluate the relationship between vagally-mediated HRV (vmHRV) parameters and the placebo response size, while also assessing sex differences in this relationship.

Results and Discussion

This revealed a positive association between vmHRV and the degree of pain relief, and this effect was driven by men. These results not only reveal new insights into the (sex-specific) mechanisms of placebo hypoalgesia, but also suggest that measuring vmHRV may be helpful in predicting placebo responsiveness. Given that placebo hypoalgesic effects contribute substantially to treatment outcomes, such a non-invasive and easily obtained predictor would be valuable in the context of personalized medicine.

Increased Beat-to-Beat Blood Pressure Variability Is Associated With Impaired Cognitive Function

BACKGROUND

Emerging evidence has linked visit-to-visit, day-to-day and 24-h ABPM blood pressure variability (BPV) with cognitive impairment. Few studies have, however, considered beat-to-beat BPV. This study, therefore, evaluated the relationship between beat-to-beat BPV and cognitive function among community-dwellers aged 55 years and over.

METHODS

Data was obtained from the Malaysian Elders Longitudinal Research (MELoR) study, which employed random stratified sampling from three parliamentary constituencies within the Klang Valley. Beat-to-beat blood pressure (BP) was recorded using non-invasive BP monitoring (TaskforceTM, CNSystems). Low frequency (LF), high frequency (HF) and low-to-high frequency (LF:HF) ratio for BPV were derived using fast Fourier transformation. Cognition was evaluated using the Montreal Cognitive Assessment (MoCA) test, and categorized into normal aging, mild impairment and moderate-to-severe impairment.

RESULTS

Data from 1,140 individuals, mean age (SD) 68.48 (7.23) years, were included. Individuals with moderate-to-severe impairment had higher HF-BPV for systolic (SBP) and diastolic (DBP) blood pressure compared to individuals within the normal aging group [OR (95% CI) = 2.29 (1.62-3.24)] and [OR (95% CI) = 1.80 (1.32-2.45)], while HF-SBPV [OR (95% CI) = 1.41 (1.03-1.93)] but not HF-DBPV was significantly higher with mild impairment compared to normal aging after adjustments for potential confounders. Moderate-to-severe impairment was associated with significantly lower LF:HF-SBPV [OR (95% CI) = 0.29 (0.18-0.47)] and LF:HF-DBPV [OR (95% CI) = 0.49 (0.34-0.72)], while mild impairment was associated with significantly lower LF:HF-SBPV [OR (95% CI) = 0.52 (0.34-0.80)] but not LF:HF-DBPV [OR (95% CI) = 0.81 (0.57-1.17)], compared to normal aging with similar adjustments.

CONCLUSION

Higher HF-BPV, which indicates parasympathetic activation, and lower LF:HF-BPV, which addresses sympathovagal balance, were observed among individuals with moderate-to-severe cognitive impairment. Future studies should determine whether BPV could be a physiological marker or modifiable risk factor for cognitive decline.

Feasibility of Ultra-Short-Term Analysis of Heart Rate and Systolic Arterial Pressure Variability at Rest and during Stress via Time-Domain and Entropy-Based Measures

Heart Rate Variability (HRV) and Blood Pressure Variability (BPV) are widely employed tools for characterizing the complex behavior of cardiovascular dynamics. Usually, HRV and BPV analyses are carried out through short-term (ST) measurements, which exploit ~five-minute-long recordings. Recent research efforts are focused on reducing the time series length, assessing whether and to what extent Ultra-Short-Term (UST) analysis is capable of extracting information about cardiovascular variability from very short recordings. In this work, we compare ST and UST measures computed on electrocardiographic R-R intervals and systolic arterial pressure time series obtained at rest and during both postural and mental stress. Standard time-domain indices are computed, together with entropy-based measures able to assess the regularity and complexity of cardiovascular dynamics, on time series lasting down to 60 samples, employing either a faster linear parametric estimator or a more reliable but time-consuming model-free method based on nearest neighbor estimates. Our results are evidence that shorter time series down to 120 samples still exhibit an acceptable agreement with the ST reference and can also be exploited to discriminate between stress and rest. Moreover, despite neglecting nonlinearities inherent to short-term cardiovascular dynamics, the faster linear estimator is still capable of detecting differences among the conditions, thus resulting in its suitability to be implemented on wearable devices.

Heart and Breathing Rate Variations as Biomarkers for Anxiety Detection

With advances in portable and wearable devices, it should be possible to analyze and interpret the collected biosignals from those devices to tailor a psychological intervention to help patients. This study focuses on detecting anxiety by using a portable device that collects electrocardiogram (ECG) and respiration (RSP) signals. The feature extraction focused on heart-rate variability (HRV) and breathing-rate variability (BRV). We show that a significant change in these signals occurred between the non-anxiety-induced and anxiety-induced states. The HRV biomarkers were the mean heart rate (MHR; p¯ = 0.04), the standard deviation of the heart rate (SD; p¯ = 0.01), and the standard deviation of NN intervals (SDNN; p¯ = 0.03) for ECG signals, and the mean breath rate (MBR; p¯ = 0.002), the standard deviation of the breath rate (SD; p¯ < 0.0001), the root mean square of successive differences (RMSSD; p¯ < 0.0001) and SDNN (p¯ < 0.0001) for RSP signals. This work extends the existing literature on the relationship between stress and HRV/BRV by being the first to introduce a transitional phase. It contributes to systematically processing mental and emotional impulse data in humans measured via ECG and RSP signals. On the basis of these identified biomarkers, artificial-intelligence or machine-learning algorithms, and rule-based classification, the automated biosignal-based psychological assessment of patients could be within reach. This creates a broad basis for detecting and evaluating psychological abnormalities in individuals upon which future psychological treatment methods could be built using portable and wearable devices.

How Reliable Are Ultra-Short-Term HRV Measurements during Cognitively Demanding Tasks?

Ultra-short-term HRV features assess minor autonomous nervous system variations such as variations resulting from cognitive stress peaks during demanding tasks. Several studies compare ultra-short-term and short-term HRV measurements to investigate their reliability. However, existing experiments are conducted in low cognitively demanding environments. In this paper, we propose to evaluate these measurements' reliability under cognitively demanding tasks using a near real-life setting. For this purpose, we selected 31 HRV features, extracted from data collected from 21 programmers performing code comprehension, and compared them across 18 different time frames, ranging from 3 min to 10 s. Statistical significance and correlation tests were performed between the features extracted using the larger window (3 min) and the same features extracted with the other 17 time frames. We paired these analyses with Bland-Altman plots to inspect how the extraction window size affects the HRV features. The main results show 13 features that presented at least 50% correlation when using 60-second windows. The HF and mNN features achieved around 50% correlation using a 30-second window. The 30-second window was the smallest time frame considered to have reliable measurements. Furthermore, the mNN feature proved to be quite robust to the shortening of the time resolution.

Heart-brain synchronization breakdown in Parkinson's disease

Heart rate variability (HRV) abnormalities are potential early biomarkers in Parkinson’s disease (PD) but their relationship with central autonomic network (CAN) activity is not fully understood. We analyzed the synchronization between HRV and brain activity in 31 PD patients and 21 age-matched healthy controls using blood-oxygen-level-dependent (BOLD) signals from resting-state functional brain MRI and HRV metrics from finger plethysmography recorded for 7.40 min. We additionally quantified autonomic symptoms (SCOPA-AUT) and objective autonomic cardiovascular parameters (blood pressure and heart rate) during deep breathing, Valsalva, and head-up tilt, which were used to classify the clinical severity of dysautonomia. We evaluated HRV and BOLD signals synchronization (HRV-BOLD-sync) with Pearson lagged cross-correlations and Fisher’s statistics for combining window-length-dependent HRV-BOLD-Sync Maps and assessed their association with clinical dysautonomia. HRV-BOLD-sync was lower significantly in PD than in controls in various brain regions within CAN or in networks involved in autonomic modulation. Moreover, heart-brain synchronization index (HBSI), which quantifies heart-brain synchronization at a single-subject level, showed an inverse exposure–response relationship with dysautonomia severity, finding the lowest HBSI in patients with severe dysautonomia, followed by moderate, mild, and, lastly, controls. Importantly, HBSI was associated in PD, but not in controls, with Valsalva pressure recovery time (sympathetic), deep breathing E/I ratio (cardiovagal), and SCOPA-AUT. Our findings support the existence of heart-brain de-synchronization in PD with an impact on clinically relevant autonomic outcomes.

Development of Autonomic Nervous System Assays as Point-of-Care Tests to Supplement Clinical Judgment in Risk Assessment for Suicidal Behavior: A Review

PURPOSE OF REVIEW

A biomarker point-of-care (POC) test that supplements the psychiatric interview and improves detection of patients at risk for suicide would be of value, and assays of autonomic nervous system (ANS) activity would satisfy the logistical requirements for a POC test. We performed a selective review of the available literature of ANS assays related to risk for suicide.

RECENT FINDINGS

We searched PubMed and Web of Science with the strategy: "suicide OR suicidal" AND "electrodermal OR heart rate variability OR pupillometry OR pupillography." The search produced 119 items, 21 of which provided original data regarding ANS methods and suicide. These 21 studies included 6 for electrodermal activity, 14 for heart rate variability, and 1 for the pupillary light reflex. The 21 papers showed associations between ANS assays and suicide risk in a direction suggesting underlying hyperarousal in patients at risk for suicide. ANS assays show promise for future development as POC tests to supplement clinical decision making in estimating risk for suicide.

Heart rate variability: A biomarker of selective response to mindfulness-based treatment versus fluoxetine in generalized anxiety disorder

BACKGROUND

Mindfulness-based interventions (MBIs) are effective for some, but not all patients with anxiety disorders, but no clinical features have been consistently able to differentiate which patients are more likely to respond. In this study, we tested heart rate variability (HRV), a proposed correlate of regulated emotional response, as a moderator of treatment response to an MBI compared with pharmacotherapy.

METHODS

Seventy-seven patients with GAD had HRV data collected before randomization to pharmacological treatment with fluoxetine or Body-in-Mind Training (an MBI focused on bodily movement attention). HRV was used to predict treatment response measured by the Hamilton anxiety rating scale at 0 (baseline), 5, and 8 weeks (end of the intervention).

RESULTS

The HF (nu) index of HRV was a strong moderator of treatment response between BMT and fluoxetine (estimate = 4.27 95%CI [1.19, 8.19]). Although fluoxetine was overall slightly superior to BMT in this study, no differences were found between groups in patients with high HF (nu) scores (estimate = -1.85 CI95% [-9.21, 5.52]). In contrast, patients with low HF (nu) achieved lower anxiety rating scores with fluoxetine treatment when compared with BMT (estimate = -10.29, 95% CI [-17.59, -2.99]).

LIMITATIONS

A relatively small sample of patients was included.

CONCLUSIONS

HRV was able to identify a subgroup for which MBI was less effective than pharmacotherapy and is a promising candidate as a selective biomarker for treatment response between an MBI and fluoxetine.

Effects of ECG Data Length on Heart Rate Variability among Young Healthy Adults

The relationship between the robustness of HRV derived by linear and nonlinear methods to the required minimum data lengths has yet to be well understood. The normal electrocardiography (ECG) data of 14 healthy volunteers were applied to 34 HRV measures using various data lengths, and compared with the most prolonged (2000 R peaks or 750 s) by using the Mann-Whitney U test, to determine the 0.05 level of significance. We found that SDNN, RMSSD, pNN50, normalized LF, the ratio of LF and HF, and SD1 of the Poincaré plot could be adequately computed by small data size (60-100 R peaks). In addition, parameters of RQA did not show any significant differences among 60 and 750 s. However, longer data length (1000 R peaks) is recommended to calculate most other measures. The DFA and Lyapunov exponent might require an even longer data length to show robust results. Conclusions: Our work suggests the optimal minimum data sizes for different HRV measures which can potentially improve the efficiency and save the time and effort for both patients and medical care providers.

Notification alert! Effects of auditory text alerts on attention and heart rate variability across three developmental periods

In a modern world saturated with cellphone-related stimuli, surprisingly little is known about their psychological effects. A small number of previous studies have found global distracting effects of cellphone rings on cognitive performance in undergraduate students. However, moment-to-moment reactions to cellphone sounds have not been investigated, nor have physiological changes that might accompany the cognitive effects. Developmental variations also remain unexamined. Thus, two experiments were conducted to examine the effects of cellphone notification sounds on cognitive performance (i.e., reaction time and accuracy on math problems) and heart rate variability in three age groups: adolescents (mean age: 15 years); young adults (mean age: 20 years); and mid-life adults (mean age: 48 years). Effects were most pronounced in the adolescent group, whose math problem accuracy and reaction time was compromised in response to notification sounds. These compromises were accompanied by increases in heart rate variability.

Multimodal Assessment of the Pulse Rate Variability Analysis Module of a Photoplethysmography-Based Telemedicine System

Alterations of heart rate variability (HRV) are associated with various (patho)physiological conditions; therefore, HRV analysis has the potential to become a useful diagnostic module of wearable/telemedical devices to support remote cardiovascular/autonomic monitoring. Continuous pulse recordings obtained by photoplethysmography (PPG) can yield pulse rate variability (PRV) indices similar to HRV parameters; however, it is debated whether PRV/HRV parameters are interchangeable. In this study, we assessed the PRV analysis module of a digital arterial PPG-based telemedical system (SCN4ALL). We used Bland–Altman analysis to validate the SCN4ALL PRV algorithm to Kubios Premium software and to determine the agreements between PRV/HRV results calculated from 2-min long PPG and ECG captures recorded simultaneously in healthy individuals (n = 33) at rest and during the cold pressor test, and in diabetic patients (n = 12) at rest. We found an ideal agreement between SCN4ALL and Kubios outputs (bias < 2%). PRV and HRV parameters showed good agreements for interbeat intervals, SDNN, and RMSSD time-domain variables, for total spectral and low-frequency power (LF) frequency-domain variables, and for non-linear parameters in healthy subjects at rest and during cold pressor challenge. In diabetics, good agreements were observed for SDNN, LF, and SD2; and moderate agreement was observed for total power. In conclusion, the SCN4ALL PRV analysis module is a good alternative for HRV analysis for numerous conventional HRV parameters.

Heart Rate Variability in Psychology: A Review of HRV Indices and an Analysis Tutorial

The use of heart rate variability (HRV) in research has been greatly popularized over the past decades due to the ease and affordability of HRV collection, coupled with its clinical relevance and significant relationships with psychophysiological constructs and psychopathological disorders. Despite the wide use of electrocardiograms (ECG) in research and advancements in sensor technology, the analytical approach and steps applied to obtain HRV measures can be seen as complex. Thus, this poses a challenge to users who may not have the adequate background knowledge to obtain the HRV indices reliably. To maximize the impact of HRV-related research and its reproducibility, parallel advances in users' understanding of the indices and the standardization of analysis pipelines in its utility will be crucial. This paper addresses this gap and aims to provide an overview of the most up-to-date and commonly used HRV indices, as well as common research areas in which these indices have proven to be very useful, particularly in psychology. In addition, we also provide a step-by-step guide on how to perform HRV analysis using an integrative neurophysiological toolkit, NeuroKit2.

Self-Reported Emotion Regulation Is Associated With Response to Test of Cardiac Vagal Function

Abstract. Parasympathetic function and emotional self-regulation (ESR) share neuroanatomic structures. Based on Porges’ Polyvagal Theory and the Neurovisceral Integration Model (NIM), we compared vagally mediated heart-rate variability (vmHRV) with psychometrically assessed ESR. We hypothesized that vmHRV and ESR would be associated during rest, a vagal function test, and recovery from that test. A significant association would justify the psychometric measuring of parasympathetic health, which is less burdensome than its psychophysiological assessment. Two hundred thirteen healthy males (aged: 18–26 years, M = 20.29 years) took part in the present study. They completed the Emotion Regulation Questionnaire (ERQ) and underwent the Cold Face Test (CFT) for 4 min wearing ambulatory electrocardiograms. A High frequency (HF) band was used as a measure of vmHRV before, during, and after the CFT. Associations between the HF band and ESR were analyzed with partial rank correlations. There was no significant association between ERQ scores and the response to the CFT itself. But there was an almost significant association between the ERQ scale Cognitive Appraisal and baseline vmHRV, and a significant association between Cognitive Appraisal and cardiac recovery from the CFT, that is, participants with higher scores on that ESR scale revealed a tendency to exhibit greater vmHRV during baseline and they exhibited greater vagal withdrawal during recovery from the CFT. Cognitive appraisal as a psychometrically assessed emotion regulatory process was reflected in a more flexible parasympathetic activity (i.e., better cardiac vagal health) during recovery from an exclusively physiological stressor. This lends convergent validity to self-reported emotion regulation, and justification for its use as a measure of ESR as a trait, offering further support for the Polyvagal Theory and NIM.

Ultra-short heart rate variability reliability for cardiac autonomic tone assessment in mesial temporal lobe epilepsy

Autonomic dysfunction in epilepsy is well-described. Heart rate variability (HRV) is a useful method to evaluate autonomic cardiac tone. Cardiac dysfunction may be involved in sudden unexpected death in epilepsy (SUDEP). HRV is a promising biomarker to enlighten the heart-brain axis role in SUDEP, but the required duration for a proper HRV recording in clinical routine remains unknown. This study aimed to verify the reliability of ultra-short HRV indices to evaluate cardiac autonomic tone in patients with epilepsy (PWE). Thirty-nine patients with mesial temporal lobe epilepsy (MTLE) had electrocardiogram recordings during the first day of video-EEG. Pearson's correlations were performed to evaluate the association between ultra-short HRV indices (five 1-min and five 30-s epochs) with standard time recording (5-min) and ANOVA compared the differences between mean HRV indices across epochs. Time domain (TD) indices showed higher mean r values when compared to frequency domain (FD) indices in 1-min (TD: r 0.80-0.99, FD: r 0.61-0.95) and 30-s epochs (TD: r 0.69-0.99, only high frequency: mean r values of 0.96). ANOVA evidenced that standard deviation of RR intervals and very low frequency means had at least 3 epochs significantly different for 1-min and 30-s epochs. Root mean square of the successive differences of RR intervals (rMSSD) presented higher Pearson's coefficient values and lower percentage of variation at 1-min or 30-s epochs in comparison to other HRV indices. In conclusion, rMSSD is the most reliable ultra-short HRV index for cardiac autonomic tone assessment in MTLE. The prognostic value of ultra-short HRV for cardiovascular risk evaluation in epilepsy remains to be determined in future studies.

Autonomic Dysregulation in Adolescent Concussion Is Sex- and Posture-Dependent

OBJECTIVE

To study autonomic responses to postural changes in concussed adolescents. The influence of sex was also studied.

DESIGN

Longitudinal cohort observational study.

PARTICIPANTS

Concussed adolescents (CONC; n = 65; 26 male adolescents; age 15 ± 1 years, range = 12-18 years) and a control (CTRL) group of nonconcussed adolescents of similar age and sport (CTRL; n = 54; 29 male adolescents; age 14 ± 1 years, range = 12-18 years).

INTERVENTIONS

Concussed participants were monitored through 6 weekly visits throughout usual physician care. Control participants underwent 2 visits separated by at least 1 week to account for intrapersonal variation in testing measures.

MAIN OUTCOME MEASURES

Heart rate variability as the root mean square of successive differences in R-R intervals (RMSSD), heart rate (HR), and blood pressure [mean arterial pressure (MAP) and diastolic blood pressure (DBP)] were measured in supine, sitting, and standing postures.

RESULTS

A mixed analysis of variance revealed a group × sex × posture interaction (P = 0.04) where seated values of RMSSD were less in concussed female participants versus control female participants (42 ± 4 vs 61 ± 7 ms; P = 0.01; Mann-Whitney rank test). Compared with CTRL, CONC exhibited increased pretesting seated DBP (69 ± 1 vs 74 ± 1 mm Hg; P < 0.01), MAP (83 ± 1 vs 86 ± 1 mm Hg; P = 0.02), and baseline seated HR (72 ± 1 vs 77 ± 2 bpm; P = 0.03). Values of DBP (P = 0.03) and MAP (P < 0.01) improved at clinical discharge, whereas the RMSSD in female participants did not (P > 0.5). Data are mean ± SEM.

CONCLUSIONS

A modest reduction in female cardiac autonomic regulation was observed during seated postures. Alterations in seated concussed DBP and MAP, but not RMSSD, resolved at clinical discharge (median = 37 days). The results indicate that, in adolescents, concussion may impair cardiovagal function in a sex- and posture-dependent manner. The findings also suggest that BP metrics, but not RMSSD, are associated with clinical concussion recovery.

Is Ultra-Short-Term Heart Rate Variability Valid in Non-static Conditions?

In mobile healthcare, heart rate variability (HRV) is increasingly being used in dynamic patient states. In this situation, shortening of the measurement time is required. This study aimed to validate ultra-short-term HRV in non-static conditions. We conducted electrocardiogram (ECG) measurements at rest, during exercise, and in the post-exercise recovery period in 30 subjects and analyzed ultra-short-term HRV in time and frequency domains by ECG in 10, 30, 60, 120, 180, and 240-s intervals, and compared the values to the 5-min HRV. For statistical analysis, null hypothesis testing, Cohen’s d statistics, Pearson’s correlation coefficient, and Bland-Altman analysis were used, with a statistical significance level of P < 0.05. The feasibility of ultra-short-term HRV and the minimum time required for analysis showed differences in each condition and for each analysis method. If the strict criteria satisfying all the statistical methods were followed, the ultra-short-term HRV could be derived from a from 30 to 240-s length of ECG. However, at least 120 s was required in the post-exercise recovery or exercise conditions, and even ultra-short-term HRV was not measurable in some variables. In contrast, according to the lenient criteria needed to satisfy only one of the statistical criteria, the minimum time required for ultra-short-term HRV analysis was 10–60 s in the resting condition, 10–180 s in the exercise condition, and 10–120 s in the post-exercise recovery condition. In conclusion, the results of this study showed that a longer measurement time was required for ultra-short-term HRV analysis in dynamic conditions. This suggests that the existing ultra-short-term HRV research results derived from the static condition cannot applied to the non-static conditions of daily life and that a criterion specific to the non-static conditions are necessary.

Heart Rate Dynamics During Acute Recovery From Maximal Aerobic Exercise in Young Adults

INTRODUCTION

Resting heart rate (HRrest), heart rate variability (HRV), and HR recovery (HRR) from exercise provide valuable information about cardiac autonomic control. RR-intervals during acute recovery from exercise (RRrec) are commonly excluded from HRV analyses due to issues of non-stationarity. However, the variability and complexity within these trends may provide valuable information about changes in HR dynamics.

PURPOSE

Assess the complexity of RRrec and determine what physiologic and demographic information are associated with differences in these indices in young adults.

METHODS

RR-intervals were collected throughout maximal treadmill exercise and recovery in young adults (n = 92). The first 5 min of RRrec were (1) analyzed with previously reported methods that use 3-interval lengths for comparison and (2) detrended using both differencing(diff) and polynomial regression(res). The standard deviation of the normal interval (SDNN), root mean square of successive differences (rMSSD), root mean square (RMS) of the residual of regression, and sample entropy (SampEn) were calculated. Repeated measures analysis of covariance (ANCOVA) tested for differences in these indices for each of the methodological approaches, controlling for race, body fat, peak oxygen uptake (VO2p eak), and resting HR (HRrest). Statistical significance was set at p < 0.05.

RESULTS

VO2p eak and HRrest were significantly correlated with traditional measures of HRR and the variability surrounding RRrec. SampEndiff and SampEnres were correlated with VO2p eak but not HRrest or HRR. The residual-method provided a significantly (p = 0.04) lower mean standard error (MSE) (0.064 ± 0.042) compared to the differencing-method (0.100 ± 0.033).

CONCLUSIONS

Complexity analysis of RRrec provides unique information about cardiac autonomic regulation immediately following the cessation of exercise when compared to traditional measures of HRR and both HRrest and VO2peak influence these results.

A Critical Review of Ultra-Short-Term Heart Rate Variability Norms Research

Heart rate variability (HRV) is the fluctuation in time between successive heartbeats and is defined by interbeat intervals. Researchers have shown that short-term (∼5-min) and long-term (≥24-h) HRV measurements are associated with adaptability, health, mobilization, and use of limited regulatory resources, and performance. Long-term HRV recordings predict health outcomes heart attack, stroke, and all-cause mortality. Despite the prognostic value of long-term HRV assessment, it has not been broadly integrated into mainstream medical care or personal health monitoring. Although short-term HRV measurement does not require ambulatory monitoring and the cost of long-term assessment, it is underutilized in medical care. Among the diverse reasons for the slow adoption of short-term HRV measurement is its prohibitive time cost (∼5 min). Researchers have addressed this issue by investigating the criterion validity of ultra-short-term (UST) HRV measurements of less than 5-min duration compared with short-term recordings. The criterion validity of a method indicates that a novel measurement procedure produces comparable results to a currently validated measurement tool. We evaluated 28 studies that reported UST HRV features with a minimum of 20 participants; of these 17 did not investigate criterion validity and 8 primarily used correlational and/or group difference criteria. The correlational and group difference criteria were insufficient because they did not control for measurement bias. Only three studies used a limits of agreement (LOA) criterion that specified a priori an acceptable difference between novel and validated values in absolute units. Whereas the selection of rigorous criterion validity methods is essential, researchers also need to address such issues as acceptable measurement bias and control of artifacts. UST measurements are proxies of proxies. They seek to replace short-term values which, in turn, attempt to estimate long-term metrics. Further adoption of UST HRV measurements requires compelling evidence that these metrics can forecast real-world health or performance outcomes. Furthermore, a single false heartbeat can dramatically alter HRV metrics. UST measurement solutions must automatically edit artifactual interbeat interval values otherwise HRV measurements will be invalid. These are the formidable challenges that must be addressed before HRV monitoring can be accepted for widespread use in medicine and personal health care.

On the Variability of Heart Rate Variability-Evidence from Prospective Study of Healthy Young College Students

Heart rate variability (HRV) has been widely used as indices for autonomic regulation, including linear analyses, entropy and multi-scale entropy based nonlinear analyses, and however, it is strongly influenced by the conditions under which the signal is being recorded. To investigate the variability of healthy HRV under different settings, we recorded electrocardiograph (ECG) signals from 56 healthy young college students (20 h for each participant) at campus using wearable single-lead ECG device. Accurate R peak to R peak (RR) intervals were extracted by combing the advantages of five commonly used R-peak detection algorithms to eliminate data quality influence. Thorough and detailed linear and nonlinear HRV analyses were performed. Variability of HRV metrics were evaluated from five categories: (1) different states of daily activities; (2) different recording time period in the same day during free-running daily activities; (3) body postures of sitting and lying; (4) lying on the left, right and back; and (5) gender influence. For most of the analyzed HRV metrics, significant differences (p < 0.05) were found among different recording conditions within the five categories except lying on different positions. Results suggested that the standardization of ECG data collection and HRV analysis should be implemented in HRV related studies, especially for entropy and multi-scale entropy based analyses. Furthermore, this preliminary study provides reference values of HRV indices under various recording conditions of healthy young subjects that could be useful information for different applications (e.g., health monitoring and management).

Binary symbolic dynamics analysis to detect stress-associated changes of nonstationary heart rate variability

Psychological stress may have harmful physiological effects and result in deteriorating health. Acute psychological stress acts also on cardiac autonomic regulation and may lead to nonstationarities in the interbeat interval series. We address the requirement of stationary RR interval series to calculate frequency domain parameters of heart rate variability (HRV) and use binary symbolic dynamics derived from RR interval differences to overcome this obstacle. 24 healthy subjects (12 female, 20–35 years) completed the following procedure: waiting period, Trier Social Stress Test to induce acute psychological stress, recovery period. An electrocardiogram was recorded throughout the procedure and HRV parameters were calculated for nine 5-min periods. Nonstationarities in RR interval series were present in all periods. During acute stress the average RR interval and SDNN decreased compared to rest before and after the stress test. Neither low frequency oscillations (LF), high frequency oscillations (HF) nor LF/HF could unambiguously reflect changes during acute stress in comparison to rest. Pattern categories derived from binary symbolic dynamics clearly identified acute stress and accompanying alterations of cardiac autonomic regulation. Methods based on RR interval differences like binary symbolic dynamics should be preferred to overcome issues related to nonstationarities.

Reliability of ultra-short indices for autonomic dysfunction in dyslipidemia

Dyslipidemia is associated with autonomic nervous system (ANS) dysfunction. Heart rate variability (HRV) is a powerful tool for evaluating the ANS and for cardiovascular risk stratification. Yet, the methodologies used are impractical in most clinical settings and therefore, are usually not applied. The current study aimed to evaluate the reliability of ultra-short HRV parameters, which are easily calculated from any standard ECG, as a practical method for ANS study, with a focus on patients with dyslipidemia. Fifty-nine volunteers with dyslipidemia underwent HRV study of parametric and power spectral indices according to accepted methods. Correlations were calculated between ultra-short HRV indices (five 1-min and five 10-s segments) and standard 5-min recordings. Correlations were found between 10-s and 1-min RMSSD and 5-min recordings (mean Pearson ρ correlation coefficients of 0.913 and 0.944, respectively, and mean concordance correlation coefficients of 0.855 and 0.938, respectively). Associations were found between other ultra-short HRV parameters (SDNN, maximum RR, minimum RR, pNN50, ln(RMSSD) and 5-min recordings. In addition, average RR, HRV-TI, NN50, TP, LF/HF, ln(SDNN), ln(HRV-TI), ln(TP) and ln(LF/HF) from 1-min recordings were associated with 5-min values. In conclusion, some ultra-short HRV parameters can be used for ANS evaluation and presumably, for cardiovascular risk stratification among patients with dyslipidemia. These parameters seem to be of great practical value for both inpatient and outpatient settings, because most can be calculated from a standard 10-s ECG strip. The prognostic implications of ECG-derived, ultra-short HRV parameters in patients with dyslipidemia should be further evaluated in future studies.

Quantifying the lagged Poincaré plot geometry of ultrashort heart rate variability series: automatic recognition of odor hedonic tone

The application of Poincaré plot analysis to characterize inter-beat interval dynamics has been successfully proposed in the scientific literature for the assessment of humans' physiological states and related aberrations. In this study, we proposed novel descriptors to trace the evolution of Poincaré plot shape over the lags. Their reliability in ultra-short cardiovascular series analysis was validated on synthetic inter-beat series generated through a physiologically plausible integral pulse frequency modulation model. Furthermore, we used the proposed approach for the investigation of the direct relationship between autonomic nervous system (ANS) dynamics and hedonic olfactory elicitation, in a group of 30 healthy subjects. Participants with a similar olfactory threshold were selected, and were asked to score 5-s stimuli in terms of arousal and valence levels according to the Russell's circumflex model of affect. Their ANS response was investigated in 35-s windows after the elicitation. Experimental results showed a gender-specific, high discriminant power of the proposed approach, discerning between pleasant and unpleasant odorants with an accuracy of 83.33% and 73.33% for men and for women, respectively. Graphical Abstract Olfaction plays a crucial role in our life and is strictly related to the Autonomic Nervous System (ANS) activity, which can be monitored studying Heart Rate Variability. We used the Lagged Poincare Plot approach to recognize gender-specific ANS response in 35-second windows after the elicitation through pleasant/unpleasant odorants.

Pitfall of heart rate variability analyses for autonomic nervous system activity with photoplethysmography

The purpose of this study is to measure the temporary intervals between R peak with ECG and pulse peak with photoplethysmography (PPG) and then to compare their precisions of two types of heart rate variability (HRV) analyses, power spectral analysis and Tone-Entropy analysis. A lot of papers used to measure cardiac autonomic nervous system (CANS) activity with HRV from PPI without awareness of the issue on another variability except CANS activity. Fifteen young male subjects were participated in this study. Simultaneous PPG and ECG were recorded with a portable device in three different postures; supine, sitting and upright positions. Our results show that, although there are no significant differences on heart rate between R-R interval (RRI) and pulse peak interval (PPI), analytic outputs on HRV analyses between RRI and PPI are different; especially, in upright position, there are significant differences on LF and HF (p<; 0.05) and also Tone-Entropy plots are clearly distant between RRI and PPI. In conclusion, our results indicate that PPG should not be used for measurement of CANS activity from HRV because of analytic error depending on physiological states like posture change though PPG probably has little problem to be used as a heart rate monitor.

Reliability of ultrashort electrocardiographic indices in hypertension: the quest for a clinically applicable prognostic marker

Heart rate variability (HRV) is an accepted clinical tool for evaluating autonomic nervous system function and a marker of adverse cardiac outcome. Although 5 min long HRV recordings are considered methodologically acceptable, it remains impractical in most clinical settings. Also, while some ultrashort HRV (usHRV) parameters were found useful in healthy individuals, their applicability to patients with cardiovascular risk factors is largely unknown. Therefore, our goal was to evaluate the reliability of ultrashort ECG (usECG) indices for HRV among patients with hypertension. One-hundred and two patients with essential hypertension were included. HRV was recorded for 5 min in strictly monitored settings. HRV parameters from randomly chosen 1 min and 10 s series were analyzed. Excellent correlations were found between 1 min SD of RR interval (SDNN) (intraclass correlation coefficient (ICC) 0.973), 10 s SDNN (ICC 0.92) and 5 min SDNN results. An excellent correlation was also found between 1 min root  mean square of successive differences in RR intervals (RMSSD) (ICC 0.992), 10 s RMSSD (ICC 0.982) and 5 min RMSSD. Logarithmic transformation of ultrashort 1 min HRV-triangular index using the natural logarithm (Ln) also had excellent correlation with 5 min measurements (ICC 0.9). Also, excellent correlations were found between 10 s and 1 min Ln(RMSSD), 10 s Ln(RMSSD) and 5 min measurements. Other HRV parameters measured from 1 min and 10 s periods showed lower correlations. In conclusion, evaluation of SDNN, RMSSD or Ln(RMSSD) from 10 s ECG recordings can be used to estimate autonomic nervous system function in patients with hypertension. These appealing markers can be readily calculated from any standard ECG tracing. The prognostic significance of ultrashort SDNN and ultrashort RMSSD in patients with cardiovascular risk factors needs to be determined in future prospective cohort studies.

Higher postictal parasympathetic activity following greater ictal heart rate increase in right- than left-sided seizures

OBJECTIVES

The objectives of this study were to determine how hemispheric laterality of seizure activity influences periictal heart rate variability (HRV) and investigate the ability of HRV parameters to discriminate right- and left-sided seizures.

METHODS

Long-term video electroencephalogram-electrocardiogram recordings of 54 focal seizures in 25 patients with focal epilepsy were reviewed. Using linear mixed models, we examined the effect of seizure laterality on linear (standard deviation of R-R intervals [SDNN], root mean square of successive differences [RMSSD], low frequency [LF] and high frequency [HF] power of HRV, and LF/HF) and nonlinear (standard deviation [SD]1, SD2, and SD2/SD1 derived from Poincaré plots) periictal HRV parameters, the magnitude of heart rate (HR) changes, and the onset time of increased HR. Receiver operating characteristics (ROC) were used to determine the ability of these parameters to discriminate between right- and left-sided seizures.

RESULTS

Postictal SDNN, RMSSD, LF, HF, SD1, and SD2 were higher in right- than left-sided seizures. Root mean square of successive difference and HF were decreased after left- but not right-sided seizures. Standard deviation of R-R intervals, LF, and SD1 were increased after right- but not left-sided seizures. Increased ictal HR was earlier and larger in right- than left-sided seizures. Postictal HF showed the greatest area under the ROC curve (AUC) (0.87) for discriminating right- and left-sided seizures.

CONCLUSIONS

Our data suggest that postictal parasympathetic activity is higher, whereas ictal HR increase is greater, in right- than left-sided seizures. Involvement of the right hemisphere may be associated with postictal autonomic instability. Postictal HRV parameters may provide useful information on hemispheric laterality of seizure activity.

Pre-performance Physiological State: Heart Rate Variability as a Predictor of Shooting Performance

Heart rate variability (HRV) is commonly used in sport science for monitoring the physiology of athletes but not as an indicator of physiological state from a psychological perspective. Since HRV is established to be an indicator of emotional responding, it could be an objective means of quantifying an athlete's subjective physiological state before competition. A total of 61 sport shooters participated in this study, of which 21 were novice shooters, 19 were intermediate shooters, and 21 were advanced level shooters. HRV, self-efficacy, and use of mental skills were assessed before they completed a standard shooting performance task of 40 shots, as in a competition qualifying round. The results showed that HRV was significantly positively correlated with self-efficacy and performance and was a significant predictor of shooting performance. In addition, advanced shooters were found to have significantly lower average heart rate before shooting and used more self-talk, relaxation, imagery, and automaticity compared to novice and intermediate shooters. HRV was found to be useful in identifying the physiological state of an athlete before competing, and as such, coaches and athletes can adopt practical strategies to improve the pre-performance physiological state as a means to optimize performance.

Optimal fiducial points for pulse rate variability analysis from forehead and finger photoplethysmographic signals

OBJECTIVE

The aim of this work is to evaluate and compare five fiducial points for the temporal location of each pulse wave from forehead and finger photoplethysmographic (PPG) pulse wave signals to perform pulse rate variability (PRV) analysis as a surrogate for heart rate variability (HRV) analysis.

APPROACH

Forehead and finger PPG signals were recorded during a tilt-table test simultaneously with the electrocardiogram (ECG). Artefacts were detected and removed and five fiducial points were computed: apex, middle-amplitude and foot points of the PPG signal, apex point of the first derivative signal and the intersection point of the tangent to the PPG waveform at the apex of the derivative PPG signal and the tangent to the foot of the PPG pulse, defined as the intersecting tangents method. Pulse period (PP) time interval series were obtained from both PPG signals and compared with the RR intervals obtained from the ECG. HRV and PRV signals were estimated and classical time and frequency domain indices were computed.

MAIN RESULTS

The middle-amplitude point of the PPG signal (n _M ), the apex point of the first derivative ([Formula: see text]), and the tangent intersection point (n _T ) are the most suitable fiducial points for PRV analysis, resulting in the lowest relative errors estimated between PRV and HRV indices and higher correlation coefficients and reliability indices. Statistically significant differences according to the Wilcoxon test between PRV and HRV signals were found for the apex and foot fiducial points of the PPG, as well as the lowest agreement between RR and PP series according to Bland-Altman analysis. Hence, these signals have been considered less accurate for variability analysis. In addition, the relative errors are significantly lower for n _M and [Formula: see text] using Friedman statistics with a Bonferroni multiple-comparison test, and we propose that n _M is the most accurate fiducial point. Based on our results, forehead PPG seems to provide more reliable information for a PRV assessment than finger PPG.

SIGNIFICANCE

The accuracy of the pulse wave detection depends on the morphology of the PPG. There is therefore a need to widely define the most accurate fiducial point for performing a PRV analysis under non-stationary conditions based on different PPG sensor locations and signal acquisition techniques.

Ultra-short term HRV features as surrogates of short term HRV: a case study on mental stress detection in real life

Background

This paper suggests a method to assess the extent to which ultra-short Heart Rate Variability (HRV) features (less than 5 min) can be considered as valid surrogates of short HRV features (nominally 5 min). Short term HRV analysis has been widely investigated for mental stress assessment, whereas the validity of ultra-short HRV features remains unclear. Therefore, this study proposes a method to explore the extent to which HRV excerpts can be shortened without losing their ability to automatically detect mental stress.

Methods

ECGs were acquired from 42 healthy subjects during a university examination and resting condition. 23 features were extracted from HRV excerpts of different lengths (i.e., 30 s, 1 min, 2 min, 3 min, and 5 min). Significant differences between rest and stress phases were investigated using non-parametric statistical tests at different time-scales. Features extracted from each ultra-short length were compared with the standard short HRV features, assumed as the benchmark, via Spearman’s rank correlation analysis and Bland-Altman plots during rest and stress phases. Using data-driven machine learning approaches, a model aiming to detect mental stress was trained, validated and tested using short HRV features, and assessed on the ultra-short HRV features.

Results

Six out of 23 ultra-short HRV features (MeanNN, StdNN, MeanHR, StdHR, HF, and SD2) displayed consistency across all of the excerpt lengths (i.e., from 5 to 1 min) and 3 out of those 6 ultra-short HRV features (MeanNN, StdHR, and HF) achieved good performance (accuracy above 88%) when employed in a well-dimensioned automatic classifier.

Conclusion

This study concluded that 6 ultra-short HRV features are valid surrogates of short HRV features for mental stress investigation.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0742-y) contains supplementary material, which is available to authorized users.

Large-scale wearable data reveal digital phenotypes for daily-life stress detection

Physiological signals have shown to be reliable indicators of stress in laboratory studies, yet large-scale ambulatory validation is lacking. We present a large-scale cross-sectional study for ambulatory stress detection, consisting of 1002 subjects, containing subjects' demographics, baseline psychological information, and five consecutive days of free-living physiological and contextual measurements, collected through wearable devices and smartphones. This dataset represents a healthy population, showing associations between wearable physiological signals and self-reported daily-life stress. Using a data-driven approach, we identified digital phenotypes characterized by self-reported poor health indicators and high depression, anxiety and stress scores that are associated with blunted physiological responses to stress. These results emphasize the need for large-scale collections of multi-sensor data, to build personalized stress models for precision medicine.

Effects of Cold Stimulation on Cardiac-Vagal Activation in Healthy Participants: Randomized Controlled Trial

Background

The experience of psychological stress has not yet been adequately tackled with digital technology by catering to healthy individuals who wish to reduce their acute stress levels. For the design of digitally mediated solutions, physiological mechanisms need to be investigated that have the potential to induce relaxation with the help of technology. Research has shown that physiological mechanisms embodied in the face and neck regions are effective for diminishing stress-related symptoms. Our study expands on these areas with the design for a wearable in mind. As this study charts new territory in research, it also is a first evaluation of the viability for a wearables concept to reduce stress.

Objective

The objectives of this study were to assess whether (1) heart rate variability would increase and (2) heart rate would decrease during cold stimulation using a thermode device compared with a (nonstimulated) control condition. We expected effects in particular in the neck and cheek regions and less in the forearm area.

Methods

The study was a fully randomized, within-participant design. Volunteer participants were seated in a laboratory chair and tested with cold stimulation on the right side of the body. A thermode was placed on the neck, cheek, and forearm. We recorded and subsequently analyzed participants’ electrocardiogram. The cold stimulation was applied in 16-second intervals over 4 trials per testing location. The control condition proceeded exactly like the cold condition, except we manipulated the temperature variable to remain at the baseline temperature. We measured heart rate as interbeat intervals in milliseconds and analyzed root mean square of successive differences to index heart rate variability. We analyzed data using a repeated-measures ANOVA (analysis of variance) approach with 2 repeated-measures factors: body location (neck, cheek, forearm) and condition (cold, control).

Results

Data analysis of 61 participants (after exclusion of outliers) showed a main effect and an interaction effect for body location and for condition, for both heart rate and heart rate variability. The results demonstrate a pattern of cardiovascular reactivity to cold stimulation, suggesting an increase in cardiac-vagal activation. The effect was significant for cold stimulation in the lateral neck area.

Conclusions

The results confirmed our main hypothesis that cold stimulation at the lateral neck region would result in higher heart rate variability and lower heart rate than in the control condition. This sets the stage for further investigations of stress reduction potential in the neck region by developing a wearable prototype that can be used for cold application. Future studies should include a stress condition, test for a range of temperatures and durations, and collect self-report data on perceived stress levels to advance findings.

Linear and non-linear heart rate metrics for the assessment of anaesthetists' workload during general anaesthesia

BACKGROUND

Excessive workload may impact the anaesthetists' ability to adequately process information during clinical practice in the operation room and may result in inaccurate situational awareness and performance. This exploratory study investigated heart rate (HR), linear and non-linear heart rate variability (HRV) metrics and subjective ratings scales for the assessment of workload associated with the anaesthesia stages induction, maintenance and emergence.

METHODS

HR and HRV metrics were calculated based on five min segments from each of the three anaesthesia stages. The area under the receiver operating characteristics curve (AUC) of the investigated metrics was calculated to assess their ability to discriminate between the stages of anaesthesia. Additionally, a multiparametric approach based on logistic regression models was performed to further evaluate whether linear or non-linear heart rate metrics are suitable for the assessment of workload.

RESULTS

Mean HR and several linear and non-linear HRV metrics including subjective workload ratings differed significantly between stages of anaesthesia. Permutation Entropy (PeEn, AUC=0.828) and mean HR (AUC=0.826) discriminated best between the anaesthesia stages induction and maintenance. In the multiparametric approach using logistic regression models, the model based on non-linear heart rate metrics provided a higher AUC compared with the models based on linear metrics.

CONCLUSIONS

In this exploratory study based on short ECG segment analysis, PeEn and HR seem to be promising to separate workload levels between different stages of anaesthesia. The multiparametric analysis of the regression models favours non-linear heart rate metrics over linear metrics.

Investigation of Lagged Poincaré Plot reliability in ultra-short synthetic and experimental Heart Rate Variability series

This study reports on the reliability of Lagged Poincaré Plot (LPP) parameters calculated from ultra-short cardiovascular time series (from 30 to 180 seconds). ity (HRV) signals, whereas a few studies have studied nonlinear approaches. Particularly, methods derived from the phase-space theory, especially the ones employing multi-lag analyses, are usually considered to be inaccurate with a low number of samples. Here we propose a comprehensive study about LPP, using both synthetic and real RR series. Specifically, we considered 109 5-minutes HRV series: 60 synthetic series generated through the Integral Pulse Frequency Modulation (IPFM) model and 49 experimental series acquired from healthy subjects during resting-state. Three parameters have been extracted through the ellipse-fitting method, SD1, SD2 and S, using ten values of lag. All LPP parameters were estimated by averaging estimates gathered from segments of 30, 120 and 180 seconds, and compared with the once from 5-minute series. Results showed Spearman's correlation coefficients higher than 0.9 in both synthetic and real series. In conclusion, SD1 gave promising results in terms of percentage absolute error, when it was extracted from series with a duration less than three minutes.

Ultra-short-term heart rate variability during resistance exercise in the elderly

Despite the appeal of ultra-short-term heart rate variability (HRV) methods of analysis applied in the clinical and research settings, the number of studies that have investigated HRV by analyzing R-R interval (RRi) recordings shorter than 5 min is still limited. Moreover, ultra-short-term HRV analysis has not been extensively validated during exercise and, currently, no indications exist for its applicability during resistance exercise. The aim of the present study was to compare ultra-short-term HRV analysis with standard short-term HRV analysis during low-intensity, dynamic, lower limb resistance exercise in healthy elderly subjects. Heart rate (HR) and RRi signals were collected from 9 healthy elderly men during discontinuous incremental resistance exercise consisting of 4-min intervals at low intensities (10, 20, 30, and 35% of 1-repetition maximum). The original RRi signals were segmented into 1-, 2-, and 3-min sections. HRV was analyzed in the time domain (root mean square of the of differences between adjacent RRi, divided by the number of RRi, minus one [RMSSD]), RRi mean value and standard deviation [SDNN] (percentage of differences between adjacent NN intervals that are greater than 50 ms [pNN50]), and by non-linear analysis (short-term RRi standard deviation [SD1] and long-term RRi standard deviation [SD2]). No significant difference was found at any exercise intensity between the results of ultra-short-term HRV analysis and the results of standard short-term HRV analysis. Furthermore, we observed excellent (0.70 to 0.89) to near-perfect (0.90 to 1.00) concordance between linear and non-linear parameters calculated over 1- and 2-min signal sections and parameters calculated over 3-min signal sections. Ultra-short-term HRV analysis appears to be a reliable surrogate of standard short-term HRV analysis during resistance exercise in healthy elderly subjects.

Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations

Ultra-short heart rate variability (HRV) analysis refers to the study of HRV features in excerpts of length <5 min. Ultra-short HRV is widely growing in many healthcare applications for monitoring individual's health and well-being status, especially in combination with wearable sensors, mobile phones, and smart-watches. Long-term (nominally 24 h) and short-term (nominally 5 min) HRV features have been widely investigated, physiologically justified and clear guidelines for analysing HRV in 5 min or 24 h are available. Conversely, the reliability of ultra-short HRV features remains unclear and many investigations have adopted ultra-short HRV analysis without questioning its validity. This is partially due to the lack of accepted algorithms guiding investigators to systematically assess ultra-short HRV reliability. This Letter critically reviewed the existing literature, aiming to identify the most suitable algorithms, and harmonise them to suggest a standard protocol that scholars may use as a reference in future studies. The results of the literature review were surprising, because, among the 29 reviewed papers, only one paper used a rigorous method, whereas the others employed methods that were partially or completely unreliable due to the incorrect use of statistical tests. This Letter provides recommendations on how to assess ultra-short HRV features reliably and proposes an inclusive algorithm that summarises the state-of-the-art knowledge in this area.

Physiological and self-report responses of parents of children with autism spectrum disorder to children crying

Little is known about the physiological response of parents of children with Autism Spectrum Disorder (ASD) to crying of children who have already received the diagnosis of ASD. This study aimed to compare cardiac dynamics via Inter-Beat Interval (IBI) and self-reported emotional states of parents of children with ASD and of parents with typically developing (TD) children while listening to crying of children with ASD (ASD cry) and of typically developing children (TD cry). Analyses revealed higher IBI in parents of children with ASD than IBI in parents of TD children while listening to both cry groups; however no differences on self-reported emotional states were observed. Parents of children with ASD were calmer (higher IBI) than parents of TD children while listening to crying. However, ASD cry did not elicit different IBI compared to TD cry. ASD cry and TD cry were differentiated based on parents' self-responses about what they felt during the listening of crying, their physiological responses showed no differences. These results highlight the similarities and differences between self-reported emotional states and physiological responses of parents of children with ASD, and also point to the importance of monitoring parents' physiological responses in addition to their subjective responses.

Reliability of the Parabola Approximation Method in Heart Rate Variability Analysis Using Low-Sampling-Rate Photoplethysmography

Photoplethysmographic signals are useful for heart rate variability analysis in practical ambulatory applications. While reducing the sampling rate of signals is an important consideration for modern wearable devices that enable 24/7 continuous monitoring, there have not been many studies that have investigated how to compensate the low timing resolution of low-sampling-rate signals for accurate heart rate variability analysis. In this study, we utilized the parabola approximation method and measured it against the conventional cubic spline interpolation method for the time, frequency, and nonlinear domain variables of heart rate variability. For each parameter, the intra-class correlation, standard error of measurement, Bland-Altman 95% limits of agreement and root mean squared relative error were presented. Also, elapsed time taken to compute each interpolation algorithm was investigated. The results indicated that parabola approximation is a simple, fast, and accurate algorithm-based method for compensating the low timing resolution of pulse beat intervals. In addition, the method showed comparable performance with the conventional cubic spline interpolation method. Even though the absolute value of the heart rate variability variables calculated using a signal sampled at 20 Hz were not exactly matched with those calculated using a reference signal sampled at 250 Hz, the parabola approximation method remains a good interpolation method for assessing trends in HRV measurements for low-power wearable applications.

An Overview of Heart Rate Variability Metrics and Norms

Healthy biological systems exhibit complex patterns of variability that can be described by mathematical chaos. Heart rate variability (HRV) consists of changes in the time intervals between consecutive heartbeats called interbeat intervals (IBIs). A healthy heart is not a metronome. The oscillations of a healthy heart are complex and constantly changing, which allow the cardiovascular system to rapidly adjust to sudden physical and psychological challenges to homeostasis. This article briefly reviews current perspectives on the mechanisms that generate 24 h, short-term (~5 min), and ultra-short-term (<5 min) HRV, the importance of HRV, and its implications for health and performance. The authors provide an overview of widely-used HRV time-domain, frequency-domain, and non-linear metrics. Time-domain indices quantify the amount of HRV observed during monitoring periods that may range from ~2 min to 24 h. Frequency-domain values calculate the absolute or relative amount of signal energy within component bands. Non-linear measurements quantify the unpredictability and complexity of a series of IBIs. The authors survey published normative values for clinical, healthy, and optimal performance populations. They stress the importance of measurement context, including recording period length, subject age, and sex, on baseline HRV values. They caution that 24 h, short-term, and ultra-short-term normative values are not interchangeable. They encourage professionals to supplement published norms with findings from their own specialized populations. Finally, the authors provide an overview of HRV assessment strategies for clinical and optimal performance interventions.

Heart rate variability metrics for fine-grained stress level assessment

BACKGROUND AND OBJECTIVES

In spite of the existence of a multitude of techniques that allow the estimation of stress from physiological indexes, its fine-grained assessment is still a challenge for biomedical engineering. The short-term assessment of stress condition overcomes the limits to stress characterization with long blocks of time and allows to evaluate the behaviour change in real-world settings and also the stress level dynamics. The aim of the present study was to evaluate time and frequency domain and nonlinear heart rate variability (HRV) metrics for stress level assessment using a short-time window.

METHODS

The electrocardiogram (ECG) signal from 14 volunteers was monitored using the Vital Jacket^TM while they performed the Trier Social Stress Test (TSST) which is a standardized stress-inducing protocol. Window lengths from 220 s to 50 s for HRV analysis were tested in order to evaluate which metrics could be used to monitor stress levels in an almost continuous way.

RESULTS

A sub-set of HRV metrics (AVNN, rMSSD, SDNN and pNN20) showed consistent differences between stress and non-stress phases, and showed to be reliable parameters for the assessment of stress levels in short-term analysis.

CONCLUSIONS

The AVNN metric, using 50 s of window length analysis, showed that it is the most reliable metric to recognize stress level across the four phases of TSST and allows a fine-grained analysis of stress effect as an index of psychological stress and provides an insight into the reaction of the autonomic nervous system to stress.

Reliability of Lagged Poincaré Plot Parameters in Ultrashort Heart Rate Variability Series: Application on Affective Sounds

The number of studies about ultrashort cardiovascular time series is increasing because of the demand for mobile applications in telemedicine and e-health monitoring. However, the current literature still needs a proper validation of heartbeat nonlinear dynamics assessment from ultrashort time series. This paper reports on the reliability of the Lagged Poincaré Plot (LPP) parameters-calculated from ultrashort cardiovascular time series. Reliability is studied on simulated as well as on real RR series. Simulated RR series are generated and LPP parameters estimated for ultrashort time series (from 15 to 60 s) are compared to those estimated from 1 h. All LPP parameters estimated from time series longer than 35 s presented a Spearman's correlation coefficient higher than 0.99. RR series acquired from 32 healthy subjects during 5-min resting state sessions are used to test the LPP approach in experimental data. The usefulness of ultrashort term parameters in real data is accomplished also studying their ability to discriminate positive and negative valence of auditory stimuli taken from the International Affective Digitized Sound System (IADS) dataset. The achieved accuracies in the recognition of elicitation along the valence dimension, using only the LPP parameters, were of 77.78% for 1 min 28 s series, and of 79.17% for 35 s series.

Heart Rate and Respiratory Rate Influence on Heart Rate Variability Repeatability: Effects of the Correction for the Prevailing Heart Rate

Background: Since heart rate variability (HRV) is associated with average heart rate (HR) and respiratory rate (RespRate), alterations in these parameters may impose changes in HRV. Hence the repeatability of HRV measurements may be affected by differences in HR and RespRate. The study aimed to evaluate HRV repeatability and its association with changes in HR and RespRate.

Methods: Forty healthy volunteers underwent two ECG examinations 7 days apart. Standard HRV indices were calculated from 5-min ECG recordings. The ECG-derived respiration signal was estimated to assess RespRate. To investigate HR impact on HRV, HRV parameters were corrected for prevailing HR.

Results: Differences in HRV parameters between the measurements were associated with the changes in HR and RespRate. However, in multiple regression analysis only HR alteration proved to be independent determinant of the HRV differences—every change in HR by 1 bpm changed HRV values by 16.5% on average. After overall removal of HR impact on HRV, coefficients of variation of the HRV parameters significantly dropped on average by 26.8% (p < 0.001), i.e., by the same extent HRV reproducibility improved. Additionally, the HRV correction for HR decreased association between RespRate and HRV.

Conclusions: In stable conditions, HR but not RespRate is the most powerful factor determining HRV reproducibility and even a minimal change of HR may considerably alter HRV. However, the removal of HR impact may significantly improve HRV repeatability. The association between HRV and RespRate seems to be, at least in part, HR dependent.

Test-Retest Reliability of Pediatric Heart Rate Variability: A Meta-Analysis

Heart rate variability (HRV), an established index of autonomic cardiovascular modulation, is associated with health outcomes (e.g., obesity, diabetes) and mortality risk. Time- and frequency-domain HRV measures are commonly reported in longitudinal adult and pediatric studies of health. While test-retest reliability has been established among adults, less is known about the psychometric properties of HRV among infants, children, and adolescents. The objective was to conduct a meta-analysis of the test-retest reliability of time- and frequency-domain HRV measures from infancy to adolescence. Electronic searches (PubMed, PsycINFO; January 1970-December 2014) identified studies with nonclinical samples aged ≤ 18 years; ≥ 2 baseline HRV recordings separated by ≥ 1 day; and sufficient data for effect size computation. Forty-nine studies (N = 5,170) met inclusion criteria. Methodological variables coded included factors relevant to study protocol, sample characteristics, electrocardiogram (ECG) signal acquisition and preprocessing, and HRV analytical decisions. Fisher's Z was derived as the common effect size. Analyses were age-stratified (infant/toddler < 5 years, n = 3,329; child/adolescent 5-18 years, n = 1,841) due to marked methodological differences across the pediatric literature. Meta-analytic results revealed HRV demonstrated moderate reliability; child/adolescent studies (Z = 0.62, r = 0.55) had significantly higher reliability than infant/toddler studies (Z = 0.42, r = 0.40). Relative to other reported measures, HF exhibited the highest reliability among infant/toddler studies (Z = 0.42, r = 0.40), while rMSSD exhibited the highest reliability among child/adolescent studies (Z = 1.00, r = 0.76). Moderator analyses indicated greater reliability with shorter test-retest interval length, reported exclusion criteria based on medical illness/condition, lower proportion of males, prerecording acclimatization period, and longer recording duration; differences were noted across age groups. HRV is reliable among pediatric samples. Reliability is sensitive to pertinent methodological decisions that require careful consideration by the researcher. Limited methodological reporting precluded several a priori moderator analyses. Suggestions for future research, including standards specified by Task Force Guidelines, are discussed.

Respiratory sinus arrhythmia in growth restricted fetuses with normal Doppler hemodynamic indices

BACKGROUND

The autonomic behavior of growth-restricted fetuses at different evolving hemodynamic stages has not been fully elicited.

AIM

To analyze the respiratory sinus arrhythmia (RSA) of growth-restricted fetuses that despite this severe condition show normal Doppler hemodynamics.

SUBJECTS

10 growth-restricted fetuses (FGR group) with normal arterial pulsatility indices (umbilical, uterine, middle cerebral, ductus venosus and aortic isthmus), and 10 healthy fetuses (Control group), 32-37weeks of gestation.

METHOD

B-mode ultrasound images for visualizing fetal breathing movements (FBM) or breathing akinesis (FBA), and the simultaneous RR-interval time series from maternal abdominal ECG recordings were obtained. The root-mean-square of successive differences of RR-intervals (RMSSD) was considered as a RSA-related parameter among the instantaneous amplitude of the high-frequency component (AMPHF) and its corresponding instantaneous frequency (IFHF), both computed by using empirical mode decomposition. Mean fetal heart-periods and RSA-related parameters were assessed during episodes of FBM and FBA in 30s length windows.

RESULTS

FGR and Control groups presented RSA-related fluctuations during FBM and FBA. Also, both groups showed significant higher (p<0.001) values for the mean heart-period, RMSSD and AMPHF during FBM. No-significant differences (p>0.05) were found for the IFHF regardless of breathing activity (FBM vs. FBA).

CONCLUSION

Growth-restricted fetuses without evident hemodynamic compromise exhibit a preserved autonomic cardiovascular regulation, characterized by higher values of RSA and mean heart-period in the presence of FBM. This physiological response reflects a compensatory strategy that may contribute to preserve blood flow redistribution to vital organs.

Hyperbilirubinemia and phototherapy in newborns: Effects on cardiac autonomic control

BACKGROUND

Neonatal jaundice and its phototherapeutic treatment can lead to several side effects involving activation of autonomic control mechanisms.

AIM

The aims of this study are to investigate the autonomic nervous system changes in icteric neonates using heart rate variability (HRV) and to assess the effect of phototherapy on short-term heart rate dynamics as an indicator of autonomic nervous control of cardiovascular system.

METHODS

HRV recordings from 20 icteric full-term neonates before, during and after phototherapy and from 20 healthy controls were analyzed. In addition to traditional time and frequency domain measures, heart rate complexity parameters including normalized complexity index (NCI), normalized unpredictability index (NUPI), pattern classification indices (0V%, 1V%, 2LV%, 2UV%) and irreversibility index (P%) on four time scales were evaluated. All measures were derived from data segments of 1000 RR intervals.

RESULTS

The analysis revealed higher values of 1V%, 2LV%, and lower P% in neonates with hyperbilirubinemia compared to controls. While HRV magnitude did not change, mean heart rate increased during and after the phototherapy. Nonlinear analysis showed a decrease of complexity, unpredictability and pattern classification measures 2LV% and 2UV%. In contrast, 0V% and irreversibility index P% were increased during and at least 30min after phototherapy.

CONCLUSION

The results suggest a shifted autonomic balance in icteric neonates compared to the controls and its further alterations during phototherapy. As the nonlinear HRV parameters are independent of the linear methods, they can provide new information about the cardiac regulatory mechanisms and their changes in neonates.

Reliability of ultra-short-term analysis as a surrogate of standard 5-min analysis of heart rate variability

BACKGROUND

Despite the increasing demands of ultra-short-term heart rate (HR) variability (HRV) for practical ambulatory applications, there have been few studies that have investigated R-R interval recording for less than 5 min for HRV analysis. It has not been extensively validated, and, currently, no normative data for ultra-short-term HRV exist. The aim of this study was to investigate the relationship between standard 5-min and ultra-short-term HRV by collecting data from a large population consisting of a wide range of age groups.

MATERIALS AND METHODS

The 5-min R-R interval series were obtained from 467 healthy volunteers ranging from 8 to 69 years of age. The original R-R interval was segmented into 270, 240, 210, 180, 150, 120, 90, 60, 30, 20, and 10 s, and those HRV features most commonly reported within the literature were calculated and compared with those using the original 5-min R-R interval series. The Pearson correlation r, the p value by the Kruskal-Wallis test, and the Bland-Altman plot analysis computations were performed for each HRV variable calculated using different lengths of R-R interval series.

RESULTS

For each HRV variable, the minimum length of the R-R interval required to reliably estimate the 5-min HRV was identified. The results were different for each age group: 10 s for HR, 20 s for high-frequency, 30 s for root mean square difference, 60 s for proportion of the number of interval differences of successive NN intervals greater than 50 ms divided by total number of NNs, 90 s for low-frequency, normalized low-frequency, normalized high-frequency, and low-frequency/high-frequency, 240 s for standard deviation of successive NN interval differences and time-frequency, and 270 s for very low-frequency. In addition, the reference value for short-term HRV from normal healthy subjects was also presented.

CONCLUSIONS

Some HRV variables calculated from R-R interval series shorter than 5 min were well matched with those calculated from the 5-min R-R interval. Thus, ultra-short-term HRV is likely to be a good surrogate method to assess trends in HRV.

Heart rate variability stabilization in athletes: towards more convenient data acquisition

Resting heart rate variability (HRV) is a potentially useful marker to consider for monitoring training status in athletes. However, traditional HRV data collection methodology requires a 5-min recording period preceded by a 5-min stabilization period. This lengthy process may limit HRV monitoring in the field due to time constraints and high compliance demands of athletes. Investigation into more practical methodology for HRV data acquisitions is required. The aim of this study was to determine the time course for stabilization of ECG-derived lnRMSSD from traditional HRV recordings. Ten-minute supine ECG measures were obtained in ten male and ten female collegiate cross-country athletes. The first 5 min for each ECG was separately analysed in successive 1-min intervals as follows: minutes 0-1 (lnRMSSD0-1 ), 1-2 (lnRMSSD1-2 ), 2-3 (lnRMSSD2-3 ), 3-4 (lnRMSSD3-4 ) and 4-5 (lnRMSSD4-5 ). Each 1-min lnRMSSD segment was then sequentially compared to lnRMSSD of the 5- to 10-min ECG segment, which was considered the criterion (lnRMSSDC riterion ). There were no significant differences between each 1-min lnRMSSD segment and lnRMSSDC riterion , and the effect sizes were considered trivial (ES ranged from 0·07 to 0·12). In addition, the ICC for each 1-min segment compared to the criterion was near perfect (ICC values ranged from 0·92 to 0·97). The limits of agreement between the prerecording values and lnRMSSDC riterion ranged from ±0·28 to ±0·45 ms. These results lend support to shorter, more convenient ECG recording procedures for lnRMSSD assessment in athletes by reducing the prerecording stabilization period to 1 min.