Ability of short-time Fourier transform method to detect transient changes in vagal effects on hearts: a pharmacological blocking study

An event-based analysis of maternal physiological reactivity following aversive child behaviors

Research investigating the association between parents' physiological reactivity and their ability to self-regulate in parenting contexts typically examines the average physiological response across the duration of a dyadic task, conflating reactivity across a multitude of parent and child behaviors. The present study utilized a moving-window analytical technique to generate a continuous, second × second time series of mothers' high-frequency heart rate variability (HF-HRV) to conduct an event-based analysis of maternal reactivity in the 10 s following an aversive child event. Analyses examined whether maternal reactivity related to parenting behaviors similarly among maltreating (n = 48) and non-maltreating (n = 29) mother-preschooler dyads. Results indicate that maternal behavior was not associated with average HF-HRV reactivity, but mothers who demonstrated an increase in HF-HRV immediately following a negative child event were more likely to engage in behaviors to return the dyad to a positive state. Findings were specific to incidents of negative child behavior, and results were not moderated by maltreatment status. These results highlight the value of using an event-based design to isolate reactivity in response to targeted events to understand how physiological reactivity supports parenting.

Comparison of nonparametric and parametric methods for time-frequency heart rate variability analysis in a rodent model of cardiovascular disease

The aim of time-varying heart rate variability spectral analysis is to detect and quantify changes in the heart rate variability spectrum components during nonstationary events. Of the methods available, the nonparametric short-time Fourier Transform and parametric time-varying autoregressive modeling are the most commonly employed. The current study (1) compares short-time Fourier Transform and autoregressive modeling methods influence on heart rate variability spectral characteristics over time and during an experimental ozone exposure in mature adult spontaneously hypertensive rats, (2) evaluates the agreement between short-time Fourier Transform and autoregressive modeling method results, and (3) describes the advantages and disadvantages of each method. Although similar trends were detected during ozone exposure, statistical comparisons identified significant differences between short-time Fourier Transform and autoregressive modeling analysis results. Significant differences were observed between methods for LF power (p ≤ 0.014); HF power (p ≤ 0.011); total power (p ≤ 0.027); and normalized HF power (p = 0.05). Furthermore, inconsistencies between exposure-related observations accentuated the lack of agreement between short-time Fourier Transform and autoregressive modeling overall. Thus, the short-time Fourier Transform and autoregressive modeling methods for time-varying heart rate variability analysis could not be considered interchangeable for evaluations with or without interventions that are known to affect cardio-autonomic activity.

Heart rate variability as a biomarker for anorexia nervosa: A review

OBJECTIVE

Anorexia nervosa (AN) typically begins in early adolescence and other than weight status has few reliable biomarkers. Early diagnosis is a critical prognostic factor, but this can be clinically challenging. Heart rate variability (HRV), the beat-by-beat variance in heart rate (HR), may provide a unique assessment for the presence of AN because it has clinical utility as a biomarker of cardiac autonomic control in various populations (e.g., athletes, the aged, those with cardiovascular diseases, etc.). We present a review of the literature examining HRV in those with AN.

METHOD

Relevant publications were selected from PubMed using the search terms 'anorexia nervosa AND (HR OR HRV)'. Twenty papers were selected and reviewed.

RESULTS

The majority of studies suggest that those with AN have markedly and consistently elevated HRV compared to controls, even greater than among young athletes. However, no studies have explored HRV as a biomarker for AN.

DISCUSSION

Future studies on HRV should elucidate its role as a diagnostic biomarker for AN as well as its responsiveness with serial measurement to track response rates and predict relapse.

Early Detection of Sudden Cardiac Death by Using Ensemble Empirical Mode Decomposition-Based Entropy and Classical Linear Features From Heart Rate Variability Signals

Sudden cardiac death (SCD), which can deprive a person of life within minutes, is a destructive heart abnormality. Thus, providing early warning information for patients at risk of SCD, especially those outside hospitals, is essential. In this study, we investigated the performances of ensemble empirical mode decomposition (EEMD)-based entropy features on SCD identification. EEMD-based entropy features were obtained by using the following technology: (1) EEMD was performed on HRV beats to decompose them into intrinsic mode functions (IMFs), (2) five entropy parameters, namely Rényi entropy (RenEn), fuzzy entropy (FuEn), dispersion Entropy (DisEn), improved multiscale permutation entropy (IMPE), and Renyi distribution entropy(RdisEn), were computed from the first four IMFs obtained, which were named EEMD-based entropy features. Additionally, an automated scheme combining EEMD-based entropy and classical linear (time and frequency domains) features was proposed with the intention of detecting SCD early by analyzing 14 min (at seven successive intervals of 2 min) heart rate variability (HRV) in signals from a normal population and subjects at risk of SCD. Firstly, EEMD-based entropy and classical linear measurements were extracted from HRV beats, and then the integrated measurements were ranked by various methodologies, i.e., t-test, entropy, receiver-operating characteristics (ROC), Wilcoxon, and Bhattacharyya. Finally, these ranked features were fed into a k-Nearest Neighbor algorithm for classification. Compared with several state-of-the-art methods, the proposed scheme firstly predicted subjects at risk of SCD up to 14 min earlier with an accuracy of 96.1%, a sensitivity of 97.5%, and a specificity of 94.4% 14 min before SCD onset. The simulation results exhibited that EEMD-based entropy estimators showed significant difference between SCD patients and normal individuals and outperformed the classical linear estimators in SCD detection, the EEMD-based FuEn and IMPE indexes were particularly useful assessments for identification of patients at risk of SCD and can be used as novel indices to reveal the disorders of rhythm variations of the autonomic nervous system when affected by SCD.

Cardiac Autonomic Responses during Exercise and Post-exercise Recovery Using Heart Rate Variability and Systolic Time Intervals-A Review

Cardiac parasympathetic activity may be non-invasively investigated using heart rate variability (HRV), although HRV is not widely accepted to reflect sympathetic activity. Instead, cardiac sympathetic activity may be investigated using systolic time intervals (STI), such as the pre-ejection period. Although these autonomic indices are typically measured during rest, the “reactivity hypothesis” suggests that investigating responses to a stressor (e.g., exercise) may be a valuable monitoring approach in clinical and high-performance settings. However, when interpreting these indices it is important to consider how the exercise dose itself (i.e., intensity, duration, and modality) may influence the response. Therefore, the purpose of this investigation was to review the literature regarding how the exercise dosage influences these autonomic indices during exercise and acute post-exercise recovery. There are substantial methodological variations throughout the literature regarding HRV responses to exercise, in terms of exercise protocols and HRV analysis techniques. Exercise intensity is the primary factor influencing HRV, with a greater intensity eliciting a lower HRV during exercise up to moderate-high intensity, with minimal change observed as intensity is increased further. Post-exercise, a greater preceding intensity is associated with a slower HRV recovery, although the dose-response remains unclear. A longer exercise duration has been reported to elicit a lower HRV only during low-moderate intensity and when accompanied by cardiovascular drift, while a small number of studies have reported conflicting results regarding whether a longer duration delays HRV recovery. “Modality” has been defined multiple ways, with limited evidence suggesting exercise of a greater muscle mass and/or energy expenditure may delay HRV recovery. STI responses during exercise and recovery have seldom been reported, although limited data suggests that intensity is a key determining factor. Concurrent monitoring of HRV and STI may be a valuable non-invasive approach to investigate autonomic stress reactivity; however, this integrative approach has not yet been applied with regards to exercise stressors.

Analysis of cardiorespiratory phase coupling and cardiovascular autonomic responses during food ingestion

The present study analyzed whether the phase coherency (λ) of respiratory sinus arrhythmia (RSA) is altered by food ingestion in healthy young subjects. After 5min of resting control, 13 healthy volunteers were asked to eat a solid meal with access to water at their own pace, followed by 5min of the postprandial state. The R-R interval (RRI), beat-to-beat blood pressure (BP), and respiratory activity were recorded using electrocardiography, a Finapres device, and inductance plethysmography, respectively. The stroke volume was calculated by the pulse-contour method from continuous BP measurement, and the cardiac output (CO) was obtained by multiplying the stroke volume by the heart rate. From the oscillatory signals of RSA and respiration, λ was computed; additionally, frequency domain indexes of the heart rate variability (HRV) were calculated using a short-time Fourier transform. A steady-state 3-min resting period (R), food ingestion period (FOOD), and the first 2-min and the last 3-min of the post prandial period were analyzed separately. We also compared the responses to gum chewing (GUM) and water intake (WATER) using the same protocol on separate days. A shortening of RRI and increases in BP and CO were observed in FOOD compared to R, suggesting a shift of sympathovagal balance toward sympathetic activation. Similar responses but smaller magnitudes were observed in the GUM condition, whereas only transient shortening of RRI was observed in the WATER condition. The HRV indexes did not show any significant changes in response to GUM and WATER but sympathovagal balance was shifted in favor of sympathetic dominance in FOOD. λ decreased during all of the conditions. There was a significant negative correlation between λ and the indirect measure of sympathovagal balance. These results suggest that ingestion of food induces enhanced cardiac sympathetic activity and that a phase coherence of RSA could provide a sensitive measure for evaluating the cardiac autonomic profile.

Complexity and time asymmetry of heart rate variability are altered in acute mental stress

We aimed to study the complexity and time asymmetry of short-term heart rate variability (HRV) as an index of complex neurocardiac control in response to stress using symbolic dynamics and time irreversibility methods. ECG was recorded at rest and during and after two stressors (Stroop, arithmetic test) in 70 healthy students. Symbolic dynamics parameters (NUPI, NCI, 0V%, 1V%, 2LV%, 2UV%), and time irreversibility indices (P%, G%, E) were evaluated. Additionally, HRV magnitude was quantified by linear parameters: spectral powers in low (LF) and high frequency (HF) bands. Our results showed a reduction of HRV complexity in stress (lower NUPI with both stressors, lower NCI with Stroop). Pattern classification analysis revealed significantly higher 0V% and lower 2LV% with both stressors, indicating a shift in sympathovagal balance, and significantly higher 1V% and lower 2UV% with Stroop. An unexpected result was found in time irreversibility: significantly lower G% and E with both stressors, P% index significantly declined only with arithmetic test. Linear HRV analysis confirmed vagal withdrawal (lower HF) with both stressors; LF significantly increased with Stroop and decreased with arithmetic test. Correlation analysis revealed no significant associations between symbolic dynamics and time irreversibility. Concluding, symbolic dynamics and time irreversibility could provide independent information related to alterations of neurocardiac control integrity in stress-related disease.

A novel approach to predict sudden cardiac death (SCD) using nonlinear and time-frequency analyses from HRV signals

Investigations show that millions of people all around the world die as the result of sudden cardiac death (SCD). These deaths can be reduced by using medical equipment, such as defibrillators, after detection. We need to propose suitable ways to assist doctors to predict sudden cardiac death with a high level of accuracy. To do this, Linear, Time-Frequency (TF) and Nonlinear features have been extracted from HRV of ECG signal. Finally, healthy people and people at risk of SCD are classified by k-Nearest Neighbor (k-NN) and Multilayer Perceptron Neural Network (MLP). To evaluate, we have compared the classification rates for both separate and combined Nonlinear and TF features. The results show that HRV signals have special features in the vicinity of the occurrence of SCD that have the ability to distinguish between patients prone to SCD and normal people. We found that the combination of Time-Frequency and Nonlinear features have a better ability to achieve higher accuracy. The experimental results show that the combination of features can predict SCD by the accuracy of 99.73%, 96.52%, 90.37% and 83.96% for the first, second, third and forth one-minute intervals, respectively, before SCD occurrence.

Review and classification of variability analysis techniques with clinical applications

Analysis of patterns of variation of time-series, termed variability analysis, represents a rapidly evolving discipline with increasing applications in different fields of science. In medicine and in particular critical care, efforts have focussed on evaluating the clinical utility of variability. However, the growth and complexity of techniques applicable to this field have made interpretation and understanding of variability more challenging. Our objective is to provide an updated review of variability analysis techniques suitable for clinical applications. We review more than 70 variability techniques, providing for each technique a brief description of the underlying theory and assumptions, together with a summary of clinical applications. We propose a revised classification for the domains of variability techniques, which include statistical, geometric, energetic, informational, and invariant. We discuss the process of calculation, often necessitating a mathematical transform of the time-series. Our aims are to summarize a broad literature, promote a shared vocabulary that would improve the exchange of ideas, and the analyses of the results between different studies. We conclude with challenges for the evolving science of variability analysis.

Cardiac autonomic regulation is impaired in girls with major depression

We aimed to study short-term heart rate variability (HRV) as an index of cardiac autonomic control in never-treated major depressive disorder (MDD) adolescent patients using linear and nonlinear analysis.

METHODS

We have examined 20 MDD girls and 20 healthy age-matched girls at the age of 15 to 18yr. The ECG was recorded in three positions: the 1st supine rest, orthostasis, the 2nd supine position. HRV magnitude was quantified by time and frequency-domain analysis (mean RR interval, SDRR, RMSSD, spectral powers in low [LF] and high frequency [HF] bands). In addition to linear measures, HRV complexity was assessed by nonlinear (symbolic dynamics) indices: normalized complexity index (NCI), normalized unpredictability index (NUPI), and pattern classification measures (0V%, 1V%, 2LV%, 2UV%).

RESULTS

HRV magnitude (RMSSD, SDRR, LF and HF powers) was significantly decreased in MDD group in a supine rest and after posture change. HRV complexity was significantly reduced (lower NCI) in the standing position. Pattern classification analysis revealed significantly higher 0V% and lower 2LV% in MDD group in supine position and orthostasis.

CONCLUSION

The HRV linear and nonlinear analysis revealed decreased magnitude and complexity of heart rate time series indicating altered neurocardiac regulation in girls with major depression without pharmacotherapy.

Time-frequency analysis of heart rate variability reveals cardiolocomotor coupling during dynamic cycling exercise in humans

To test the hypothesis that cycling exercise modulates heart rate variability (HRV), we applied a short-time Fourier transform on the electrocardiogram of subjects performing a maximal graded cycling test. A pedaling frequency component (PFC) in HRV was continuously observed over the time course of the exercise test and extracted from R-R interval series obtained from 15 healthy subjects with a heterogeneous physical fitness, exercising at three different pedaling frequency ( n = 5): 70, 80, and 90 rpm. From 30 to 50% of the maximal power output (Pmax), in the 90 rpm group, spectral aliasing caused PFC to overlap with the respiratory sinus arrhythmia (RSA) band, significantly overestimating the PFC amplitude ( APFC). In the meantime, APFC did not increase significantly from its minimal values in the 70 rpm (∼1.26 ms) and 80 rpm (∼1.20 ms) groups. Then, from 60 to 100% maximal power output (Pmax), workload increase caused a significant ∼2.8-, ∼3.3-, and ∼3.4-fold increase in APFC in the 70, 80, and 90 rpm groups, respectively, with no significant difference between groups. At peak exercise, APFC accounted for ∼43, ∼39, and ∼49% of the total HRV in the 70, 80, and 90 rpm groups, respectively. Our findings indicate that cycling continuously modulates the cardiac chronotropic response to exercise, inducing a new component in HRV, and that workload increase during intense exercise further accentuates this cardiolocomotor coupling. Moreover, because PFC and RSA overlapped at low workloads, methodological care should be taken in future studies aiming to quantify RSA as an index of parasympathetic activity.

Analysis of heart rate variability using time-varying frequency bands based on respiratory frequency

In this paper a methodological approach for the analysis of nonstationary heart rate variability (HRV) signals using time-varying frequency bands based on respiratory frequency is presented. Spectral analysis of HRV is accomplished by means of the Smoothed Pseudo Wigner Ville distribution. Different approaches to the definition of the low frequency (LF) and high frequency (HF) bands are considered which involve respiratory information, derived either from a respiratory signal or from the ECG itself. Results are presented which derive from recordings acquired during stress testing and induced emotion experiments.

Heart rate variability dynamics during early recovery after different endurance exercises

Since heart rate variability (HRV) during the first minutes of the recovery after exercise has barely been studied, we wanted to find out HRV dynamics immediately after five different constant-speed exercises. Thirteen sedentary women performed two low-intensity (3,500 m [3,500(LI)] and 7,000 m [7,000(LI)] at 50% of the velocity of VO(2max) [vVO(2max)]), two moderate-intensity (3,500 m [3,500(MI)] and 7,000 m [7,000(MI)] at approximately 63% vVO(2max)) and one high-intensity (3,500 m at approximately 74% vVO(2max) [3,500(HI)]) exercises on a treadmill. HRV was analyzed with short-time Fourier transform method during the 30-min recovery. High frequency power (HFP) was for the first time higher than at the end of the exercise after the first minute of the recovery (3,500(LI) and 7,000(LI), P < 0.001), after the fourth (3,500(MI), P < 0.05) and the fifth (7,000(MI), P < 0.05) minute of the recovery and at the end of the 30-min recovery (3,500(HI), P < 0.01). There were no differences in HRV between 3,500(LI) and 7,000(LI) or between 3,500(MI) and 7,000(MI) during the recovery. The levels of HFP and TP were higher during the whole recovery after 3,500(LI) compared to 3,500(MI) and 3,500(HI). We found increased HFP, presumably caused by vagal reactivation, during the first 5 min of the recovery after each exercise, except for 3,500(HI). The increased intensity of the exercise resulted in slower recovery of HFP as well as lower levels of HFP and TP when compared to low-intensity exercise. Instead, the doubled running distance had no influence on HRV recovery.

Saliva testosterone and heart rate variability in the professional symphony orchestra after "public faintings" of an orchestra member

Musicians are sensitive to changes in their work environment. A 2-year longitudinal study with repeated observations was performed in two professional symphony orchestras. A representative sample from each one of them was selected, 15 and 16 members respectively. In one of them a wind player fainted twice in front of the audience shortly preceding and coinciding with the start of the study. Changes in two indicators that reflect regenerative/anabolic and parasympathetic tone, saliva testosterone concentration (STC) and very low-frequency power (VLFP) in heart rate variability were followed in relation to this dramatic change. Saliva samples and 24-h ECG heart rate variability recordings were collected on five occasions every 6 months during a 2-year period. No changes were seen in the control orchestra whereas the levels showed a pronounced rise in the intervention orchestra during the first part of the study, starting from low levels. VLFP showed a similar pattern, with initially low and then rising level in the intervention orchestra and higher stable level in the other group. In the total study group, a rise in STC over the whole observation period was significantly correlated with increase in VLFP and also significantly correlated with a decrease in low/high-frequency power ratio in heart rate variability. The changes observed in the anabolic/regenerative STC and the parasympathetically influenced VLFP may reflect changes in the work environment associated with the faintings.