Temporal asymmetries of short-term heart period variability are linked to autonomic regulation

Fructose-1,6-bisphosphate reverses hypotensive effect caused by L-kynurenine in Wistar male rats

Hypotension is one of the main characteristics of the systemic inflammation, basically caused by endothelial dysfunction. Studies have shown that the amino acid L-kynurenine (KYN) causes vasodilation in mammals, leading to hypotensive shock. In hypotensive shock, when activated by the KYN, the voltage-gated potassium channel encoded by the family KCNQ (Kv7) gene can cause vasodilation. Fructose-1,6-bisphosphate (FBP) it is being considered in studies an anti-inflammatory, antioxidant, immunomodulator, and a modulator of some ion channels (Ca2+, Na+, and K+). We analyzed the effects of KYN and FBP on mean blood pressure (MBP), systolic and diastolic (DBP) blood pressure, and heart rate variability (HRV) in Wistar rats. Results demonstrated that the administration of KYN significant decreased MBP, DBP, and increased HRV. Importantly, the FBP treatment reversed the KYN effects on MBP, DBP, and HRV. Molecular Docking Simulations suggested that KYN and FBP present a very close estimated free energy of binding and the same position into structure of KCNQ4. Our results did demonstrate that FBP blunted the decrease in BP, provoked by KYN. Results raise new hypotheses for future and studies in the treatment of hypotension resulting from inflammation.

Validity of the Pneumonitor for Analysis of Short-Term Heart Rate Asymmetry Extended with Respiratory Data in Pediatric Cardiac Patients

Background: Wearable technologies have been developed to measure physiological parameters conveniently. To consider the new measurement device valid, the crucial point is to assess its reliability with the gold standard. The study aimed to assess the validity of the Pneumonitor (PM, fs = 250 Hz) for acquisition of 5 min RR intervals (RRi) for analysis of heart rate asymmetry (HRA) in relation to the electrocardiography (ECG, fs = 1000 Hz) in a group of 19 pediatric cardiac patients. Association between HRA and respiratory rate (RespRate) was verified. Methods: The validation comprised Bland-Altman analysis, intraclass correlation coefficient, and Student's t-test. Results: Sufficient agreement between 10 from 16 HRA parameters was observed. Different HRA parameters values calculated based on RRi from both devices were related to different results of correlation analysis between two parameters and RespRate. Conclusions: The PM might be considered valid for recording RRi, which are then processed to calculate selected HRA parameters in a group of pediatric cardiac patients in rest condition. However, RRi recorded using devices with fs < 250 Hz may be not adequate for reliable HRA analysis.

Different effects of inspiratory duration and expiratory duration on heart rate deceleration capacity and heart rate asymmetry

PURPOSE

Low values of heart rate deceleration capacity (DC) and heart rate asymmetry (HRA) are associated with cardiovascular risks. Slow respiration has been proven to enhance the magnitudes of these indexes, but individual inspiratory (TI) and expiratory (TE) durations were not controlled in most studies. This study aims to examine whether the effects of TI and TE on these indexes would be the same and, if not, how to adjust TI and TE to maximize the effect of slow respiration.

METHODS

We evaluated 14 seated healthy young adults who randomly controlled their breathing to nine combinations of TI and TE, each chosen respectively from 2, 4, and 6 s. A 5-min R-R interval time series was obtained from each study period for further analysis.

RESULTS

The magnitude of DC increased when TI or TE increased, while that of acceleration capacity (AC) remained almost unchanged by TI. We further defined a new index as 100 × DC2/(DC2 + AC2) and found it to be correlated with conventional Guzik's (r = 0.94) and Porta's (r = 0.99) indexes of HRA during different combinations of TI and TE. Increasing TI and increasing TE both enhanced the magnitudes of HRA indexes, with TI taking effect when ≤ 4 s, and TE taking effect when > 4 s. DC and HRA indexes were maximized with a TI of 4 s and a TE of 6 s.

CONCLUSION

We suggest that a TI of 3-4 s with a TE of 7-6 s is an appropriate standard for slow respiration.

Percent duration of heart rate acceleration within the respiratory cycle: a novel approach to assess heart rate asymmetry

Accelerations and decelerations of heart rate are nonsymmetrical in the magnitude and number of beat-to-beat changes. The asymmetric features of heart rate variability are related to respiratory durations. To explore the link between respiration and heart rate asymmetry (HRA), we evaluated 14 seated, healthy young adults who breathed with nine combinations of inspiration duration (TI) and expiration duration (TE), chosen respectively from 2, 4, and 6 s. A 5-min R-R interval (RRI) time series was obtained from each study period to construct an averaged pattern waveform relative to the respiratory cycle. We observed that the time interval between inspiration onset and RRI minimum progressively lengthened as TI and TE increased. The time interval between expiration onset and RRI maximum also lengthened when TE increased but shortened when TI increased. Consequently, TI and TE had different effects on the acceleration time (AT; from RRI maximum to RRI minimum) and deceleration time (DT; from RRI minimum to RRI maximum). The percentage of AT within the respiratory cycle showed a strong correlation with traditional Guzik's (r = 0.862, P < 0.001) and Porta's (r = 0.878, P < 0.001) indexes of HRA assessed in a Poincaré plot analysis. These findings suggest that, in addition to considering the magnitude and number of beat-to-beat changes, HRA can also be assessed based on another aspect: the duration of consecutive changes. The stepwise link between the duration of heart rate change and respiratory duration provides insight into the mechanisms connecting respiration to HRA.NEW & NOTEWORTHY In healthy adults who regulated their breathing across nine combinations of inspiration and expiration durations, we used averaged pattern waveform technique to quantify the durations of heart rate acceleration and deceleration within the respiratory cycle. The percent duration of acceleration showed a strong correlation with traditional heart rate asymmetry indexes, which evaluate the magnitude and number of beat-to-beat changes. This new approach opens a window to explore the asymmetric features of heart rate variability.

Permutation time irreversibility in sleep electroencephalograms: Dependence on sleep stage and the effect of equal values

Time irreversibility (TIR) refers to the manifestation of nonequilibrium brain activity influenced by various physiological conditions; however, the influence of sleep on electroencephalogram (EEG) TIR has not been sufficiently investigated. In this paper, a comprehensive study on permutation TIR (pTIR) of EEG data under different sleep stages is conducted. Two basic ordinal patterns (i.e., the original and amplitude permutations) are distinguished to simplify sleep EEGs, and then the influences of equal values and forbidden permutation on pTIR are elucidated. To detect pTIR of brain electric signals, five groups of EEGs in the awake, stages I, II, III, and rapid eye movement (REM) stages are collected from the public Polysomnographic Database in PhysioNet. Test results suggested that the pTIR of sleep EEGs significantly decreases as the sleep stage increases (p<0.001), with the awake and REM EEGs demonstrating greater differences than others. Comparative analysis and numerical simulations support the importance of equal values. Distribution of equal states, a simple quantification of amplitude fluctuations, significantly increases with the sleep stage (p<0.001). If these equalities are ignored, incorrect probabilistic differences may arise in the forward-backward and symmetric permutations of TIR, leading to contradictory results; moreover, the ascending and descending orders for symmetric permutations also lead different outcomes in sleep EEGs. Overall, pTIR in sleep EEGs contributes to our understanding of quantitative TIR and classification of sleep EEGs.

Heart rate dynamics and asymmetry during sympathetic activity stimulation and post-stimulation recovery in ski mountaineers-a pilot exploratory study

There is a lack of studies on non-linear heart rate (HR) variability in athletes. We aimed to assess the usefulness of short-term HR dynamics and asymmetry parameters to evaluate the neural modulation of cardiac activity based on non-stationary RR interval series by studying their changes during sympathetic nervous system activity stimulation (isometric handgrip test) and post-stimulation recovery in professional ski mountaineers. The correlation between the changes in the parameters and the respiratory rate (RespRate) and also the duration of the career was analyzed. Short-term (5 min) and ultra-short-term (1 min) rates of patterns with no variations (0V), number of acceleration runs of length 1 (AR1), and short-term Porta's Index were greater, whereas Guzik's Index (GI) was smaller during sympathetic stimulation compared to rest. GI increased and the number of AR1 decreased during recovery. Greater increases in GI and RMSSD were associated with greater decreases in RespRate during recovery. Greater increases in RespRate from rest to short-term sympathetic stimulation were associated with greater increases in 0V (Max-min method) and AR1 but also with greater decreases in decelerations of short-term variance and accelerations and decelerations of long-term variance. Greater increases in 0V (Max-min method) and number of AR1 during sympathetic stimulation were associated with a shorter career duration. Greater decreases in these parameters during recovery were associated with a longer career duration. Changes in measures of HR dynamics and asymmetry, calculated based on short-term non-stationary RRi time series induced by sympathetic stimulation and post-stimulation recovery, reflected sympathovagal shift and were associated with condition-related alterations in RespRate and career duration in athletes who practice ski mountaineering.

Prediction of post-operative atrial fibrillation in patients after cardiac surgery using heart rate variability

PURPOSE

Post-operative atrial fibrillation (PoAF) occurs in ~ 30% of patients after cardiac surgery. The etiology of PoAF is complex, but a disbalance in autonomic systems plays an important role. The goal of this study was to assess whether pre-operative heart rate variability analysis can predict the risk of PoAF.

METHODS

Patients without a history of AF with an indication for cardiac surgery were included. Two-hour ECG recordings one day before surgery was used for the HRV analysis. Univariate and multivariate logistic regression, including all HRV parameters, their combination, and clinical variables, were calculated to find the best predictive model for post-operative AF.

RESULTS

One hundred and thirty-seven patients (33 women) were enrolled in the study. PoAF occurred in 48 patients (35%, AF group); the remaining 89 patients were in the NoAF group. AF patients were significantly older (69.1 ± 8.6 vs. 63.4 ± 10.5 yrs., p = 0.002), and had higher CHA₂DS₂-VASc score (3 ± 1.4 vs. 2.5 ± 1.3, p = 0.01). In the multivariate regression model, parameters independently associated with higher risk of AF were pNN50, TINN, absolute power VLF, LF and HF, total power, SD2, and the Porta index. A combination of clinical variables with HRV parameters in the ROC analysis achieved an AUC of 0.86, a sensitivity of 0.95, and a specificity of 0.57 and was more effective in PoAF prediction than a combination of clinical variables alone.

CONCLUSION

A combination of several HRV parameters is helpful in predicting the risk of PoAF. Attenuation of heart rate variability increases the risk for PoAF.

Heart Rate Asymmetry, Its Compensation, and Heart Rate Variability in Healthy Adults during 48-h Holter ECG Recordings

Heart rate asymmetry (HRA) reflects different contributions of heart rate (HR) decelerations and accelerations to heart rate variability (HRV). In this study, we examined various properties of HRA, including its compensation and HRV, in 48-h electrocardiogram (ECG) recordings in healthy adults. Furthermore, we compared sex differences in parameters used to quantify HRA and HRV. Variance-based and relative HRA and HRV parameters were computed for Holter ECG recordings lasting up to 48 h in 101 healthy volunteers. The median age of the subjects was 39 years, with 47 of them being men. The prevalence of all forms of HRA was statistically different from randomness (p < 0.0001). Specifically, HR decelerations contributed >50% (C1d) to short-term HRA in 98.02% of subjects, while HR decelerations contributed <50% to long-term HRA in 89.11% of recordings and to total HRA in 88.12% of recordings. Additionally, decelerations accounted for <50% of all changing heartbeats (Porta's index) in 74.26% of subjects, and HRA compensation was present in 88.12% of volunteers. Our findings suggest that various HRA features are present in most healthy adults. While men had more pronounced HRA expression, the prevalence of short-, long-term, and total HRA and its compensation was similar in both sexes. For HRV, values of variance-based indices were higher in men than in women, but no differences were found for relative measures. In conclusion, our study references HRA and HRV for longer ECG recordings of up to 48 h, which have become increasingly important in clinical ECG monitoring. The findings can help understand and compare the characteristics of HRA and HRV in patients with different diseases.

Heart Rate Asymmetry in Healthy Children

Heart rate asymmetry (HRA) is a physiological phenomenon characterized by an unequal contribution of heart rate decelerations and accelerations to different heart rate variability (HRV) features. While HRA has been demonstrated in adults' ECGs of different duration, a similar investigation in healthy children has not been conducted. This study investigated the variance- and number-based HRA features in 96 healthy children (50 girls and 46 boys, aged 3-18 years) using 24-h ECGs. Additionally, we studied sex differences in HRA. To quantify HRA, variance-based and relative contributions of heart rate decelerations to short-term (C1d), long-term (C2d), and total (CTd) HRV, and the number of all heartbeats (Nd) were computed. Heart rate decelerations contributed more to C1d, but less to C2d and CTd, and were less frequent than heart rate accelerations. Short-term HRA was better expressed in boys. The majority of children (93.7%) had short-term HRA, 88.5% had long-term HRA, 88.5% had total HRA, and 99.0% had more accelerations than decelerations. No sex differences were observed for the rate of various HRA features. Heart rate asymmetry is a common phenomenon in healthy children, as observed in 24-h ECGs. Our findings can be used as reference data for future clinical studies on HRA in children.

Comprehensive breathing variability indices enhance the prediction of extubation failure in patients on mechanical ventilation

BACKGROUND AND OBJECTIVE

Despite the numerous studies on extubation readiness assessment for patients who are invasively ventilated in the intensive care unit, a 10-15% extubation failure rate persists. Although breathing variability has been proposed as a potential predictor of extubation failure, it is mainly assessed using simple statistical metrics applied to basic respiratory parameters. Therefore, the complex pattern of breathing variability conveyed by continuous ventilation waveforms may be underexplored.

METHODS

Here, we aimed to develop novel breathing variability indices to predict extubation failure among invasively ventilated patients. First, breath-to-breath basic and comprehensive respiratory parameters were computed from continuous ventilation waveforms 1 h before extubation. Subsequently, the basic and advanced variability methods were applied to the respiratory parameter sequences to derive comprehensive breathing variability indices, and their role in predicting extubation failure was assessed. Finally, after reducing the feature dimensionality using the forward search method, the combined effect of the indices was evaluated by inputting them into the machine learning models, including logistic regression, random forest, support vector machine, and eXtreme Gradient Boosting (XGBoost).

RESULTS

The coefficient of variation of the dynamic mechanical power per breath (CV-MPd[J/breath]) exhibited the highest area under the receiver operating characteristic curve (AUC) of 0.777 among the individual indices. Furthermore, the XGBoost model obtained the best AUC (0.902) by combining multiple selected variability indices.

CONCLUSIONS

These results suggest that the proposed novel breathing variability indices can improve extubation failure prediction in invasively ventilated patients.

An assessment of heart rate and blood pressure asymmetry in the diagnosis of vasovagal syncope in females

Introduction: Heart Rate Asymmetry (HRA) describes a phenomenon of differences between accelerations and decelerations in human heart rate. Methods used for HRA assessment can be further implemented in the evaluation of asymmetry in blood pressure variations (Blood Pressure Asymmetry-BPA). Methods: We have analyzed retrospectively the series of heartbeat intervals extracted from ECG and beat-to-beat blood pressure signals from 16 vasovagal patients (age: 32.1 ± 13.3; BMI: 21.6 ± 3.8; all female) and 19 healthy subjects (age: 34.6 ± 7.6; BMI: 22.1 ± 3.4; all female) who have undergone tilt test (70°). Asymmetry was evaluated with Poincaré plot-based methods for 5 min recordings from supine and tilt stages of the test. The analyzed biosignals were heart rate (RR), diastolic (dBP) and systolic Blood Pressure (sBP) and Pulse Pressure (PP). In the paper we explored the differences between healthy and vasovagal women. Results: The changes of HRA indicators between supine and tilt were observed only in the control group (Porta Index p = 0.026 and Guzik Index p = 0.005). No significant differences in beat-to-beat variability (i.e. spread of points across the line of identity in Poincaré plot-SD1) of dBP was noted between supine and tilt in the vasovagal group (p = 0.433 in comparison to p = 0.014 in healthy females). Moreover, in vasovagal patients the PP was significantly different (supine: 41.47; tilt: 39.27 mmHg) comparing to healthy subjects (supine: 35.87; tilt: 33.50 mmHg) in supine (p = 0.019) and in tilt (p = 0.014). Discussion: Analysis of HRA and BPA represents a promising method for the evaluation of cardiovascular response to orthostatic stressors, however currently it is difficult to determine a subject's underlying health condition based only on these parameters.

Multiscale asymmetry reveals changes in the maternal short-term heart rate dynamics of preeclamptic women during labor

BACKGROUND

It is known that acceleration and deceleration patterns in heart rate variability (HRV) are asymmetrically distributed in healthy subjects. Accordingly, novel approaches for assessing the asymmetrical properties of HRV, such as the multiscale asymmetry (MSA), have been applied in the perinatal field.

OBJECTIVE

To study the asymmetry of accelerations and decelerations of maternal short-term cardiac dynamics of thirty-six normotensive and preeclamptic women during labor/nonlabor by MSA analysis.

METHODS

The RR interval time series obtained from these participants were classified into four groups: normotensive (control) without labor C-NL, n= 10; control with labor C-L, n= 10; and two preeclamptic groups with absence or presence of labor P-NL, n= 6; and P-L, n= 10, respectively. Multiscale indices of heart rate asymmetry (HRA) such as Porta (P%), Guzik (G%) and Ehlers (E) were used to explore the changes of HRA in the normotensive and preeclamptic groups in the presence or absence of labor.

RESULTS

The main result of this study shows that preeclamptic women manifest decreased magnitude of decelerations of heart rate dynamics compared to normotensive women indicated by G% and E. We speculate that a lower cardiac parasympathetic response may be manifested in preeclamptic women during labor/nonlabor compared to normotensive women.

CONCLUSIONS

These observations represented a new insight into the autonomic cardiovascular regulation in preeclampsia, which could contribute to the perinatal field in the future.

Detection and categorization of severe cardiac disorders based solely on heart period measurements

Cardiac disorders are common conditions associated with a high mortality rate. Due to their potential for causing serious symptoms, it is desirable to constantly monitor cardiac status using an accessible device such as a smartwatch. While electrocardiograms (ECGs) can make the detailed diagnosis of cardiac disorders, the examination is typically performed only once a year for each individual during health checkups, and it requires expert medical practitioners to make comprehensive judgments. Here we describe a newly developed automated system for alerting individuals about cardiac disorders solely by measuring a series of heart periods. For this purpose, we examined two metrics of heart rate variability (HRV) and analyzed 1-day ECG recordings of more than 1,000 subjects in total. We found that a metric of local variation was more efficient than conventional HRV metrics for alerting cardiac disorders, and furthermore, that a newly introduced metric of local-global variation resulted in superior capacity for discriminating between premature contraction and atrial fibrillation. Even with a 1-minute recording of heart periods, our new detection system had a diagnostic performance even better than that of the conventional analysis method applied to a 1-day recording.

Associations between heart rate asymmetry expression and asymmetric detrended fluctuation analysis results

The relation between recently established asymmetry in Asymmetric Detrended Fluctuation Analysis (ADFA) and Heart Rate Asymmetry is studied. It is found that the ADFA asymmetric exponents are related both to the overall variability and to its asymmetric components at all studied time scales. We find that the asymmetry in scaling exponents, i.e., [Formula: see text] is associated with both variance-based and runs-based types of asymmetry. This observation suggests that the physiological mechanisms of both types are similar, even though their origins and mathematical methods are very different. The graphical abstract demonstrates strong, nonlinear association between the expression of Heart Rate Asymmetry measured using relative descriptors and the Asymmetric Detrended Fluctuation Analysis results. It is clear that there is a strong relation between the two theoretically disparate approaches to signal analysis. The technique to demonstrate the association is loess fit.

Heart rate variability as a biomarker in patients with Chronic Chagas Cardiomyopathy with or without concomitant digestive involvement and its relationship with the Rassi score

Background

Dysautonomia plays an ancillary role in the pathogenesis of Chronic Chagas Cardiomyopathy (CCC), but is the key factor causing digestive organic involvement. We investigated the ability of heart rate variability (HRV) for death risk stratification in CCC and compared alterations of HRV in patients with isolated CCC and in those with the mixed form (CCC + digestive involvement). Thirty-one patients with CCC were classified into three risk groups (low, intermediate and high) according to their Rassi score. A single-lead ECG was recorded for a period of 10–20 min, RR series were generated and 31 HRV indices were calculated. The HRV was compared among the three risk groups and regarding the associated digestive involvement. Four machine learning models were created to predict the risk class of patients.

Results

Phase entropy is decreased and the percentage of inflection points is increased in patients from the high-, compared to the low-risk group. Fourteen patients had the mixed form, showing decreased triangular interpolation of the RR histogram and absolute power at the low-frequency band. The best predictive risk model was obtained by the support vector machine algorithm (overall F1-score of 0.61).

Conclusions

The mixed form of Chagas' disease showed a decrease in the slow HRV components. The worst prognosis in CCC is associated with increased heart rate fragmentation. The combination of HRV indices enhanced the accuracy of risk stratification. In patients with the mixed form of Chagas disease, a higher degree of sympathetic autonomic denervation may be associated with parasympathetic impairment.

Analysis of Short-Term Heart Rate Asymmetry in High-Performance Athletes and Non-Athletes

Heart rate asymmetry (HRA) refers to how asymmetrically the acceleration and deceleration patterns in heartbeat fluctuations are distributed. There is limited evidence regarding HRA changes in athletes and their association with autonomic regulation. This study aimed to compare the short-term HRA of high-performance athletes and non-athletes during an autonomic function test by calculating relevant HRA measures. This exploratory study obtained beat-to-beat RR interval time series from 15 high-performance athletes and 12 non-athletes during a standardized autonomic function test. This test includes rest, postural change, controlled respiration, prolonged orthostatism, exercise, and recovery phases. The following HRA parameters were computed from the RR time series for both groups: asymmetric spread index (ASI), slope index (SI), Porta’s index (PI), Guzik’s index (GI), and Ehlers’ index (EI). We found significant differences (p < 0.01) in the mean value of several HRA parameters between athletes and non-athletes and across the autonomic function test phases, mainly in postural change and recovery phases. Our results indicate that high-performance athletes manifest a higher number and magnitude of cardiac decelerations than non-athletes after an orthostatic challenge, as indicated by GI and EI. In addition, lower HRA was found in athletes in the recovery phase than in non-athletes, as indicated by ASI.

Beyond the Baroreflex: A New Measure of Autonomic Regulation Based on the Time-Frequency Assessment of Variability, Phase Coherence and Couplings

For decades the role of autonomic regulation and the baroreflex in the generation of the respiratory sinus arrhythmia (RSA) - modulation of heart rate by the frequency of breathing - has been under dispute. We hypothesized that by using autonomic blockers we can reveal which oscillations and their interactions are suppressed, elucidating their involvement in RSA as well as in cardiovascular regulation more generally. R-R intervals, end tidal CO2, finger arterial pressure, and muscle sympathetic nerve activity (MSNA) were measured simultaneously in 7 subjects during saline, atropine and propranolol infusion. The measurements were repeated during spontaneous and fixed-frequency breathing, and apnea. The power spectra, phase coherence and couplings were calculated to characterise the variability and interactions within the cardiovascular system. Atropine reduced R-R interval variability (p < 0.05) in all three breathing conditions, reduced MSNA power during apnea and removed much of the significant coherence and couplings. Propranolol had smaller effect on the power of oscillations and did not change the number of significant interactions. Most notably, atropine reduced R-R interval power in the 0.145-0.6 Hz interval during apnea, which supports the hypothesis that the RSA is modulated by a mechanism other than the baroreflex. Atropine also reduced or made negative the phase shift between the systolic and diastolic pressure, indicating the cessation of baroreflex-dependent blood pressure variability. This result suggests that coherent respiratory oscillations in the blood pressure can be used for the non-invasive assessment of autonomic regulation.

Characterisation of neonatal cardiac dynamics using ordinal partition network

The maturation of the autonomic nervous system (ANS) starts in the gestation period and it is completed after birth in a variable time, reaching its peak in adulthood. However, the development of ANS maturation is not entirely understood in newborns. Clinically, the ANS condition is evaluated with monitoring of gestational age, Apgar score, heart rate, and by quantification of heart rate variability using linear methods. Few researchers have addressed this problem from the perspective nonlinear data analysis. This paper proposes a new data-driven methodology using nonlinear time series analysis, based on complex networks, to classify ANS conditions in newborns. We map 74 time series given by RR intervals from premature and full-term newborns to ordinal partition networks and use complexity quantifiers to discriminate the dynamical process present in both conditions. We obtain three complexity quantifiers (permutation, conditional, and global node entropies) using network mappings from forward and reverse directions, and considering different time lags and embedding dimensions. The results indicate that time asymmetry is present in the data of both groups and the complexity quantifiers can differentiate the groups analysed. We show that the conditional and global node entropies are sensitive for detecting subtle differences between the neonates, particularly for small embedding dimensions (m < 7). This study reinforces the assessment of nonlinear techniques for RR interval time series analysis. Graphical Abstract.

Assessment of time irreversibility in a time series using visibility graphs

In this paper, we studied the time-domain irreversibility of time series, which is a fundamental property of systems in a nonequilibrium state. We analyzed a subgroup of the databases provided by University of Rochester, namely from the THEW Project. Our data consists of LQTS (Long QT Syndrome) patients and healthy persons. LQTS may be associated with an increased risk of sudden cardiac death (SCD), which is still a big clinical problem. ECG-based artificial intelligence methods can identify sudden cardiac death with a high accuracy. It follows that heart rate variability contains information about the possibility of SCD, which may be extracted, provided that appropriate methods are developed for this purpose. Our aim was to assess the complexity of both groups using visibility graph (VG) methods. Multivariate analysis of connection patterns of graphs built from time series was performed using multiplex visibility graph methods. For univariate time series, time irreversibility of the ECG interval QT of patients with LQTS was lower than for the healthy. However, we did not observe statistically significant difference in the comparison of RR intervals time series of the two groups studied. The connection patterns retrieved from multiplex VGs have more similarity with each other in the case of LQTS patients. This observation may be used to develop better methods for SCD risk stratification.

The influence of external stressors on physiological testing: Implication for return-to-play protocols

External stressors such as alcohol, caffeine, and vigorous exercise are known to alter cellular homeostasis, affecting the autonomic nervous system (ANS) and overall physiological function. However, little direct evidence exists quantifying the impact of these external stressors on physiological testing. We assessed the impact of the above-listed stressors on spontaneous baroreflex sensitivity (BRS), heart rate variability (HRV), heart rate asymmetry (HRA), and systolic blood pressure variability (BPV). Seventeen male university varsity American-style football athletes completed two identical assessments on separate days, once presenting with one or more stressors (recent intake of caffeine, alcohol, or exercise participation; contraindicated assessment) and another with no stressors present (repeat assessment). Both assessments were conducted within one week and at the same time of day. The testing protocol consisted of 5-min of rest followed by 5-min of a squat-stand maneuver (0.05 Hz). Continuous beat-to-beat blood pressure and electrocardiogram measurements were collected and allowed for calculations of BRS, HRV, HRA, and BPV. Significant decreases (p < 0.05) in HRV and HRA metrics (SDNN, SD2, SDNNd, SDNNa, SD2a, SD2d), HRV total power, and BRS-up sequence were found during the contraindicated assessment in comparison to the repeat assessment. When assessing those with exercise as their only stressor, high-frequency HRV and BRS-pooled were significantly decreased and increased, respectively, during the contraindicated assessment. Pre-season physiological baseline testing in sport is becoming increasingly prevalent and thus must consider external stressors to ascertain accurate and reliable data. This data confirms the need for stringent and standardized guidelines for pre-participation baseline physiological testing.

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External stressors (exercise participation, caffeine consumption, and alcohol consumption) decrease heart rate variability and the asymmetrical contribution of heart rate accelerations and decelerations (SDNN, SD2, Total Power, SDNNd, SDNNa, SD2d, and SD2a).

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External stressors decrease spontaneous baroreflex sensitivity up-sequence, but no significant changes were found regarding systolic blood pressure variability.

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The establishment of standardized pre-participation guidelines controlling for external stressors would increase the validity and reliability of physiological testing, improving the clinical utility of such data.

Correlation between heart rate variability and polysomnography-derived scores of obstructive sleep apnea

Obstructive sleep apnea (OSA) is one of the most common sleep disorders and affects nearly a billion people worldwide. Furthermore, it is estimated that many patients with OSA are underdiagnosed, which contributes to the development of comorbidities, such as cardiac autonomic imbalance, leading to high cardiac risk. Heart rate variability (HRV) is a non-invasive, widely used approach to evaluating neural control of the heart. This study evaluates the relationship between HRV indices and the presence and severity of OSA. We hypothesize that HRV, especially the nonlinear methods, can serve as an easy-to-collect marker for OSA early risk stratification. Polysomnography (PSG) exams of 157 patients were classified into four groups: OSA-free (N = 26), OSA-mild (N = 39), OSA-moderate (N = 37), and OSA-severe (N = 55). The electrocardiogram was extracted from the PSG recordings, and a 15-min beat-by-beat series of RR intervals were generated every hour during the first 6 h of sleep. Linear and nonlinear HRV approaches were employed to calculate 32 indices of HRV. Specifically, time- and frequency-domain, symbolic analysis, entropy measures, heart rate fragmentation, acceleration and deceleration capacities, asymmetry measures, and fractal analysis. Results with indices of sympathovagal balance provided support to reinforce previous knowledge that patients with OSA have sympathetic overactivity. Nonlinear indices showed that HRV dynamics of patients with OSA display a loss of physiologic complexity that could contribute to their higher risk of development of cardiovascular disease. Moreover, many HRV indices were found to be linked with clinical scores of PSG. Therefore, a complete set of HRV indices, especially the ones obtained by the nonlinear approaches, can bring valuable information about the presence and severity of OSA, suggesting that HRV can be helpful for in a quick diagnosis of OSA, and supporting early interventions that could potentially reduce the development of comorbidities.

The effect of passive lower limb training on heart rate asymmetry

OBJECTIVE

Heart rate asymmetry (HRA) is an approach for quantitatively assessing the uneven distribution of heart rate accelerations and decelerations for sinus rhythm. We aimed to investigate whether automatic regulation led to HRA alternation during passive lower limb training.

METHODS

Thirty healthy participants were recruited in this study. The protocol included a baseline (Pre-E) and three passive lower limb training trials (E1, E2 and E3) with a randomized order. Several variance-based HRA variables were established. Heart rate variability (HRV) parameters, i.e., mean RR, SDNN, RMSSD, LF (n.u.), HF (n.u.) and VLF (ms2), and HRA variables, i.e., SD1a, SD1d, SD2a, SD2d, SDNNa and SDNNd, were calculated by using 5-min RR time series, as well as the normalized HRA variables, i.e., C1a, C1d, C2a, C2d, Ca and Cd.

RESULTS

Our results showed that the performance of HRA was distinguished. The normalized HRA was observed with significant changes in E1, E2 and E3 compared to Pre -E. Moreover, parts of non-normalized HRA variables correlated with HRV parameters, which indicated that HRA might benefit in assessing cardiovascular modulation in passive lower limb training.

CONCLUSIONS

In summary, this study suggested that passive training led to significant HRA alternation and the application of HRA gave us the possibility for autonomic assessment.

Differences in the Asymmetry of Beat-to-Beat Fetal Heart Rate Accelerations and Decelerations at Preterm and Term Active Labor

The fetal autonomic nervous system responds to uterine contractions during active labor as identified by changes in the accelerations and decelerations of fetal heart rate (FHR). Thus, this exploratory study aimed to characterize the asymmetry differences of beat-to-beat FHR accelerations and decelerations in preterm and term fetuses during active labor. In an observational study, we analyzed 10 min of fetal R-R series collected from women during active preterm labor (32–36 weeks of pregnancy, n = 17) and active term labor (38–40 weeks of pregnancy, n = 27). These data were used to calculate the Deceleration Reserve (DR), which is a novel parameter that quantifies the asymmetry of the average acceleration and deceleration capacity of the heart. In addition, relevant multiscale asymmetric indices of FHR were also computed. Lower values of DR, calculated with the input parameters of T = 50 and s = 10, were associated with labor occurring at the preterm condition (p = 0.0131). Multiscale asymmetry indices also confirmed significant (p < 0.05) differences in the asymmetry of FHR. Fetuses during moderate premature labor may experience more decaying R-R trends and a lower magnitude of decelerations compared to term fetuses. These differences of FHR dynamics might be related to the immaturity of the fetal cardiac autonomic nervous system as identified by this system response to the intense uterine activity at active labor.

Time-irreversibility test for random-length time series: The matching-time approach applied to DNA

In this work, we implement the so-called matching-time estimators for estimating the entropy rate as well as the entropy production rate for symbolic sequences. These estimators are based on recurrence properties of the system, which have been shown to be appropriate for testing irreversibility, especially when the sequences have large correlations or memory. Based on limit theorems for matching times, we derive a maximum likelihood estimator for the entropy rate by assuming that we have a set of moderately short symbolic time series of finite random duration. We show that the proposed estimator has several properties that make it adequate for estimating the entropy rate and entropy production rate (or for testing the irreversibility) when the sample sequences have different lengths, such as the coding sequences of DNA. We test our approach with controlled examples of Markov chains, non-linear chaotic maps, and linear and non-linear autoregressive processes. We also implement our estimators for genomic sequences to show that the degree of irreversibility of coding sequences in human DNA is significantly larger than that for the corresponding non-coding sequences.

Algorithmic Approaches for Assessing Irreversibility in Time Series: Review and Comparison

The assessment of time irreversibility, i.e., of the lack of invariance of the statistical properties of a system under the operation of time reversal, is a topic steadily gaining attention within the research community. Irreversible dynamics have been found in many real-world systems, with alterations being connected to, for instance, pathologies in the human brain, heart and gait, or to inefficiencies in financial markets. Assessing irreversibility in time series is not an easy task, due to its many aetiologies and to the different ways it manifests in data. It is thus not surprising that several numerical methods have been proposed in the last decades, based on different principles and with different applications in mind. In this contribution we review the most important algorithmic solutions that have been proposed to test the irreversibility of time series, their underlying hypotheses, computational and practical limitations, and their comparative performance. We further provide an open-source software library that includes all tests here considered. As a final point, we show that "one size does not fit all", as tests yield complementary, and sometimes conflicting views to the problem; and discuss some future research avenues.

EntropyHub: An open-source toolkit for entropic time series analysis

An increasing number of studies across many research fields from biomedical engineering to finance are employing measures of entropy to quantify the regularity, variability or randomness of time series and image data. Entropy, as it relates to information theory and dynamical systems theory, can be estimated in many ways, with newly developed methods being continuously introduced in the scientific literature. Despite the growing interest in entropic time series and image analysis, there is a shortage of validated, open-source software tools that enable researchers to apply these methods. To date, packages for performing entropy analysis are often run using graphical user interfaces, lack the necessary supporting documentation, or do not include functions for more advanced entropy methods, such as cross-entropy, multiscale cross-entropy or bidimensional entropy. In light of this, this paper introduces EntropyHub, an open-source toolkit for performing entropic time series analysis in MATLAB, Python and Julia. EntropyHub (version 0.1) provides an extensive range of more than forty functions for estimating cross-, multiscale, multiscale cross-, and bidimensional entropy, each including a number of keyword arguments that allows the user to specify multiple parameters in the entropy calculation. Instructions for installation, descriptions of function syntax, and examples of use are fully detailed in the supporting documentation, available on the EntropyHub website- www.EntropyHub.xyz. Compatible with Windows, Mac and Linux operating systems, EntropyHub is hosted on GitHub, as well as the native package repository for MATLAB, Python and Julia, respectively. The goal of EntropyHub is to integrate the many established entropy methods into one complete resource, providing tools that make advanced entropic time series analysis straightforward and reproducible.

Asymmetric multiscale multifractal analysis (AMMA) of heart rate variability

Objective.The physiological activity of the heart is controlled and modulated mostly by the parasympathetic and sympathetic nervous systems. Heart rate variability (HRV) analysis is therefore used to observe fluctuations that reflect changes in the activity in these two branches. Knowing that acceleration and deceleration patterns in heart rate fluctuations are asymmetrically distributed, the ability to analyze HRV asymmetry was introduced into MMA.Approach. The new method is called asymmetric multiscale multifractal analysis (AMMA) and the analysis involved six groups: 36 healthy persons, 103 cases with aortic valve stenosis, 36 with hypertrophic cardiomyopathy, 32 with atrial fibrillation, 59 patients with coronary artery disease (CAD) and 13 with congestive heart failure.Main results. Analyzing the results obtained for the 6 groups of patients based on the AMMA method, i.e. comparing the Hurst surfaces for heart rate decelerations and accelerations, it was noticed that these surfaces differ significantly. And the differences occur in most groups for large fluctuations (multifractal parameterq > 0). In addition, a similarity was found for all groups for the AMMA Hurst surface for decelerations to the MMA Hurst surface-heart rate decelerations (lengthening of the RR intervals) appears to be the main factor determining the shape of the complete Hurst surface and so the multifractal properties of HRV. The differences between the groups, especially for CAD, hypertrophic cardiomyopathy and aortic valve stenosis, are more visible if the Hurst surfaces are analyzed separately for accelerations and decelerations.Significance. The AMMA results presented here may provide additional input for HRV analysis and create a new paradigm for future medical screening. Note that the HRV analysis using MMA (without distinguishing accelerations from decelerations) gave satisfactory screening statistics in our previous studies.

Short-Term Effect of Percutaneous Coronary Intervention on Heart Rate Variability in Patients with Coronary Artery Disease

Myocardial ischemia in patients with coronary artery disease (CAD) leads to imbalanced autonomic control that increases the risk of morbidity and mortality. To systematically examine how autonomic function responds to percutaneous coronary intervention (PCI) treatment, we analyzed data of 27 CAD patients who had admitted for PCI in this pilot study. For each patient, five-minute resting electrocardiogram (ECG) signals were collected before and after the PCI procedure. The time intervals between ECG collection and PCI were both within 24 h. To assess autonomic function, normal sinus RR intervals were extracted and were analyzed quantitatively using traditional linear time- and frequency-domain measures [i.e., standard deviation of the normal-normal intervals (SDNN), the root mean square of successive differences (RMSSD), powers of low frequency (LF) and high frequency (HF) components, LF/HF] and nonlinear entropy measures [i.e., sample entropy (SampEn), distribution entropy (DistEn), and conditional entropy (CE)], as well as graphical metrics derived from Poincaré plot [i.e., Porta’s index (PI), Guzik’s index (GI), slope index (SI) and area index (AI)]. Results showed that after PCI, AI and PI decreased significantly (p < 0.002 and 0.015, respectively) with effect sizes of 0.88 and 0.70 as measured by Cohen’s d static. These changes were independent of sex. The results suggest that graphical AI and PI metrics derived from Poincaré plot of short-term ECG may be potential for sensing the beneficial effect of PCI on cardiovascular autonomic control. Further studies with bigger sample sizes are warranted to verify these observations.

Heart Rate Asymmetry Analysis During Head-Up Tilt Test in Healthy Men

The purpose of this study is to assess the cardiovascular system response to orthostatic stress in a group of 133 healthy men using heart rate asymmetry (HRA) methods. HRA is a feature of variability in human heart rate which is dependent upon external and internal body conditions. The initial phases of head-up tilt test (HUTT), namely, supine and tilt, were chosen as the external body affecting factors. Various calculation methods of HRA, such as Porta's index (PI), Guzik's index (GI), and its variance based components, were used to assess the heart rate variability (HRV) and its asymmetry. We compared 5-min ECG recordings from both supine and tilt phases of HUT test. Short-term HRA was observed in 54.1% of men in supine phase and 65.4% of men in tilt phase. The study revealed significant increase of GI (from 0.50 to 0.52, p < 0.001) in the tilt phase as well as significant changes in HRV descriptors between HUTT phases. Our results showed that the variability of human heart rate and its asymmetry are sensitive to orthostatic stress. The study of short-term HRA is a potential additional tool to increase sensitivity in conditions where HUTT is a diagnostic tool, such as vasovagal syncope.

Time-Reversibility, Causality and Compression-Complexity

Detection of the temporal reversibility of a given process is an interesting time series analysis scheme that enables the useful characterisation of processes and offers an insight into the underlying processes generating the time series. Reversibility detection measures have been widely employed in the study of ecological, epidemiological and physiological time series. Further, the time reversal of given data provides a promising tool for analysis of causality measures as well as studying the causal properties of processes. In this work, the recently proposed Compression-Complexity Causality (CCC) measure (by the authors) is shown to be free of the assumption that the "cause precedes the effect", making it a promising tool for causal analysis of reversible processes. CCC is a data-driven interventional measure of causality (second rung on the Ladder of Causation) that is based on Effort-to-Compress (ETC), a well-established robust method to characterize the complexity of time series for analysis and classification. For the detection of the temporal reversibility of processes, we propose a novel measure called the Compressive Potential based Asymmetry Measure. This asymmetry measure compares the probability of the occurrence of patterns at different scales between the forward-time and time-reversed process using ETC. We test the performance of the measure on a number of simulated processes and demonstrate its effectiveness in determining the asymmetry of real-world time series of sunspot numbers, digits of the transcedental number π and heart interbeat interval variability.

Lack of association between heart period variability asymmetry and respiratory sinus arrhythmia in healthy and chronic heart failure individuals

Temporal asymmetry is a peculiar aspect of heart period (HP) variability (HPV). HPV asymmetry (HPVA) is reduced with aging and pathology, but its origin is not fully elucidated. Given the impact of respiration on HPV resulting in the respiratory sinus arrhythmia (RSA) and the asymmetric shape of the respiratory pattern, a possible link between HPVA and RSA might be expected. In this study we tested the hypothesis that HPVA is significantly associated with RSA and asymmetry of the respiratory rhythm. We studied 42 middle-aged healthy (H) subjects, and 56 chronic heart failure (CHF) patients of whom 26 assigned to the New York Heart Association (NYHA) class II (CHF-II) and 30 to NYHA class III (CHF-III). Electrocardiogram and lung volume were monitored for 8 minutes during spontaneous breathing (SB) and controlled breathing (CB) at 15 breaths/minute. The ratio of inspiratory (INSP) to expiratory (EXP) phases, namely the I/E ratio, and RSA were calculated. HPVA was estimated as the percentage of negative HP variations, traditionally measured via the Porta’s index (PI). Departures of PI from 50% indicated HPVA and its significance was tested via surrogate data. We found that RSA increased during CB and I/E ratio was smaller than 1 in all groups and experimental conditions. In H subjects the PI was about 50% during SB and it increased significantly during CB. In both CHF-II and CHF-III groups the PI was about 50% during SB and remained unmodified during CB. The PI was uncorrelated with RSA and I/E ratio regardless of the experimental condition and group. Pooling together data of different experimental conditions did not affect conclusions. Therefore, we conclude that the HPVA cannot be explained by RSA and/or I/E ratio, thus representing a peculiar feature of the cardiac control that can be aroused in middle-aged H individuals via CB.

Maturation of the Autonomic Nervous System in Premature Infants: Estimating Development Based on Heart-Rate Variability Analysis

This study aims at investigating the development of premature infants' autonomic nervous system (ANS) based on a quantitative analysis of the heart-rate variability (HRV) with a variety of novel features. Additionally, the role of heart-rate drops, known as bradycardias, has been studied in relation to both clinical and novel sympathovagal indices. ECG data were measured for at least 3 h in 25 preterm infants (gestational age ≤32 weeks) for a total number of 74 recordings. The post-menstrual age (PMA) of each patient was estimated from the RR interval time-series by means of multivariate linear-mixed effects regression. The tachograms were segmented based on bradycardias in periods after, between and during bradycardias. For each of those epochs, a set of temporal, spectral and fractal indices were included in the regression model. The best performing model has R 2 = 0.75 and mean absolute error MAE = 1.56 weeks. Three main novelties can be reported. First, the obtained maturation models based on HRV have comparable performance to other development models. Second, the selected features for age estimation show a predominance of power and fractal features in the very-low- and low-frequency bands in explaining the infants' sympathovagal development from 27 PMA weeks until 40 PMA weeks. Third, bradycardias might disrupt the relationship between common temporal indices of the tachogram and the age of the infant and the interpretation of sympathovagal indices. This approach might provide a novel overview of post-natal autonomic maturation and an alternative development index to other electrophysiological data analysis.

PyBioS: A freeware computer software for analysis of cardiovascular signals

BACKGROUND AND OBJECTIVE

Several software applications have been proposed in the past years as computational tools for assessing biomedical signals. Many of them are focused on heart rate variability series only, with their strengths and limitations depending on the necessity of the user and the scope of the application. Here, we introduce new software, named PyBioS, intended for the analysis of cardiovascular signals, even though any type of biomedical signal can be used. PyBioS has some functionalities that differentiate it from the other software.

METHODS

PyBioS was developed in Python language with an intuitive, user-friendly graphical user interface. The basic steps for using PyBioS comprise the opening or creation (simulation) of signals, their visualization, preprocessing and analysis. Currently, PyBioS has 8 preprocessing tools and 15 analysis methods, the later providing more than 50 metrics for analysis of the signals' dynamics.

RESULTS

The possibility to create simulated signals and save the preprocessed signals is a strength of PyBioS. Besides, the software allows batch processing of files, making the analysis of a large amount of data easy and fast. Finally, PyBioS has plenty of analysis methods implemented, with the focus on nonlinear and complexity analysis of signals and time series.

CONCLUSIONS

Although PyBioS is not intended to overcome all the necessities from users, it has useful functionalities that may be helpful in many situations. Moreover, PyBioS is continuously under improvement and several simulated signals, tools and analysis methods are still to be implemented. Also, a new module is being implemented on it to provide machine learning algorithms for classification and regression of data extracted from the biomedical signals.

Entropy Analysis of RR-Time Series From Stress Tests

The RR-interval time series or tachograms obtained from electrocardiograms have been widely studied since they reflect the cardiac variability, and this is an indicative of the health status of a person. The tachogram can be seen as a highly non-linear and complex time series, and therefore, should be analyzed with non-linear techniques. In this work, several entropy measures, Sample Entropy (SampEn), Approximate Entropy (ApEn), and Fuzzy Entropy (FuzzyEn) are used as a measure of heart rate variability (HRV). Tachograms belonging to thirty-nine subjects were obtained from a cardiac stress test consisting of a rest period followed by a period of moderate physical activity. Subjects are grouped according to their physical activity using the IPAQ sedentary and active questionnaire, we work with youth and middle-aged adults. The entropy measures for each group show that for the sedentary subjects the values are high at rest and decrease appreciably with moderate physical activity, This happens for both young and middle-aged adults. These results are highly reproducible. In the case of the subjects that exercise regularly, an increase in entropy is observed or they tend to retain the entropy value that they had at rest. It seems that there is a possible correlation between the physical condition of a person with the increase or decrease in entropy during moderate physical activity with respect to the entropy at rest. It was also observed that entropy during longer physical activity tests tends to decrease as fatigue accumulates, but this decrease is small compared to the change that occurs when going from rest to physical activity.

Are Strategies Favoring Pattern Matching a Viable Way to Improve Complexity Estimation Based on Sample Entropy?

It has been suggested that a viable strategy to improve complexity estimation based on the assessment of pattern similarity is to increase the pattern matching rate without enlarging the series length. We tested this hypothesis over short simulations of nonlinear deterministic and linear stochastic dynamics affected by various noise amounts. Several transformations featuring a different ability to increase the pattern matching rate were tested and compared to the usual strategy adopted in sample entropy (SampEn) computation. The approaches were applied to evaluate the complexity of short-term cardiac and vascular controls from the beat-to-beat variability of heart period (HP) and systolic arterial pressure (SAP) in 12 Parkinson disease patients and 12 age- and gender-matched healthy subjects at supine resting and during head-up tilt. Over simulations, the strategies estimated a larger complexity over nonlinear deterministic signals and a greater regularity over linear stochastic series or deterministic dynamics importantly contaminated by noise. Over short HP and SAP series the techniques did not produce any practical advantage, with an unvaried ability to discriminate groups and experimental conditions compared to the traditional SampEn. Procedures designed to artificially increase the number of matches are of no methodological and practical value when applied to assess complexity indexes.

Yoga in school sports improves functioning of autonomic nervous system in young adults: A non-randomized controlled pilot study

Background

Yoga in school is a beneficial tool to promote the good health and well-being of students by changing the way they react to stress. The positive effects of yoga—taught in schools—on children, youth and young adults have been demonstrated in former studies using mostly subjective psychometric data.

Aim

The present trial aims to evaluate the potential effects of yoga on autonomic regulation in young adults by analyzing heart rate variability (HRV).

Methods

This study is a non-randomized, explorative, two-arm-pilot study with an active control group. Fourteen healthy young adults took part in a 10-week yoga program (90 min once a week) in school and were compared to a control group of 11 students who participated in conventional school sports (90 min once a week over 10 weeks). 24-hour electrocardiograms (ECGs) were recorded at baseline and following the 10-week intervention. From 20-minute of nocturnal sleep phases, HRV parameters were calculated from linear (time and frequency domain) and nonlinear dynamics (such as symbolic dynamics and Poincaré plot analysis). Analyses of variance (ANOVA) followed by t-tests as post-hoc tests estimating both statistical significance and effect size were used to compare pre-post-intervention for the two groups.

Results

The statistical analysis of the interaction effects did not reveal a significant group and time interaction for the individual nocturnal HRV indices. Almost all indices revealed medium and large effects regarding the time main effects. The changes in the HRV indices following the intervention were more dramatic for the yoga group than for the control group which is reflected in predominantly higher significances and stronger effect sizes in the yoga group.

Conclusion

In this explorative pilot trial, an increase of HRV (more parasympathetic dominance and overall higher HRV) after ten weeks of yoga in school in comparison to regular school sports was demonstrated, showing an improved self-regulation of the autonomic nervous system.

The control mechanisms of heart rate dynamics in a new heart rate nonlinear time series model

The control mechanisms and implications of heart rate variability (HRV) under the sympathetic (SNS) and parasympathetic nervous system (PNS) modulation remain poorly understood. Here, we establish the HR model/HRV responder using a nonlinear process derived from Newton's second law in stochastic self-restoring systems through dynamic analysis of physiological properties. We conduct model validation by testing, predictions, simulations, and sensitivity and time-scale analysis. We confirm that the outputs of the HRV responder can be accepted as the real data-generating process. Empirical studies show that the dynamic control mechanism of heart rate is a stable fixed point, rather than a strange attractor or transitions between a fixed point and a limit cycle; HR slope (amplitude) may depend on the ratio of cardiac disturbance or metabolic demand mean (standard deviation) to myocardial electrical resistance (PNS-SNS activity). For example, when metabolic demands remain unchanged, HR amplitude depends on PNS to SNS activity; when autonomic activity remains unchanged, HR amplitude during resting reflects basal metabolism. HR parameter alterations suggest that age-related decreased HRV, ultrareduced HRV in heart failure, and ultraelevated HRV in ST segment alterations refer to age-related decreased basal metabolism, impaired myocardial metabolism, and SNS hyperactivity triggered by myocardial ischemia, respectively.

Time Irreversibility of Resting-State Activity in the Healthy Brain and Pathology

Characterizing brain activity at rest is of paramount importance to our understanding both of general principles of brain functioning and of the way brain dynamics is affected in the presence of neurological or psychiatric pathologies. We measured the time-reversal symmetry of spontaneous electroencephalographic brain activity recorded from three groups of patients and their respective control group under two experimental conditions (eyes open and closed). We evaluated differences in time irreversibility in terms of possible underlying physical generating mechanisms. The results showed that resting brain activity is generically time-irreversible at sufficiently long time scales, and that brain pathology is generally associated with a reduction in time-asymmetry, albeit with pathology-specific patterns. The significance of these results and their possible dynamical etiology are discussed. Some implications of the differential modulation of time asymmetry by pathology and experimental condition are examined.

Comparison of methods for the assessment of nonlinearity in short-term heart rate variability under different physiopathological states

Despite the widespread diffusion of nonlinear methods for heart rate variability (HRV) analysis, the presence and the extent to which nonlinear dynamics contribute to short-term HRV are still controversial. This work aims at testing the hypothesis that different types of nonlinearity can be observed in HRV depending on the method adopted and on the physiopathological state. Two entropy-based measures of time series complexity (normalized complexity index, NCI) and regularity (information storage, IS), and a measure quantifying deviations from linear correlations in a time series (Gaussian linear contrast, GLC), are applied to short HRV recordings obtained in young (Y) and old (O) healthy subjects and in myocardial infarction (MI) patients monitored in the resting supine position and in the upright position reached through head-up tilt. The method of surrogate data is employed to detect the presence and quantify the contribution of nonlinear dynamics to HRV. We find that the three measures differ both in their variations across groups and conditions and in the percentage and strength of nonlinear HRV dynamics. NCI and IS displayed opposite variations, suggesting more complex dynamics in O and MI compared to Y and less complex dynamics during tilt. The strength of nonlinear dynamics is reduced by tilt using all measures in Y, while only GLC detects a significant strengthening of such dynamics in MI. A large percentage of detected nonlinear dynamics is revealed only by the IS measure in the Y group at rest, with a decrease in O and MI and during T, while NCI and GLC detect lower percentages in all groups and conditions. While these results suggest that distinct dynamic structures may lie beneath short-term HRV in different physiological states and pathological conditions, the strong dependence on the measure adopted and on their implementation suggests that physiological interpretations should be provided with caution.

Phase entropy: a new complexity measure for heart rate variability

OBJECTIVE

Information entropy is generally employed for analysing the complexity of physiological signals. However, most definitions of entropy estimate the degree of compressibility and thus quantify the randomness. Physiological signals are very complex because of nonlinear relationships and interactions between various systems and subsystems of the body. Therefore, analysis of randomness may not be sufficient to describe this complexity. To analyse the complexity of heart rate variability (HRV), a new entropy method, phase entropy (PhEn), has been proposed as a quantification of two-dimensional phase space.

APPROACH

The second-order difference plot (SODP), a two-dimensional phase space, provides a visual summary of the rate of variability. The distribution of scatter points in a SODP provides information about the dynamics of the underlying system. PhEn estimates the Shannon entropy of the weighted distribution in a coarse-grained SODP.

MAIN RESULTS

The performance of PhEn has been evaluated using simulated signals, synthetic HRV signals and real HRV signals. PhEn shows a better discriminating power and stability than other entropy measures. It is computationally efficient. Moreover, it has the ability to assess temporal asymmetry of physiological signals.

SIGNIFICANCE

PhEn quantifies the multiplicity and rate of variability associated with physiological signals. It is sensitive to time irreversibility. Therefore, it appears to be a promising tool for analysing physiological signals such as HRV.

Testing heart rate asymmetry in long, nonstationary 24 hour RR-interval time series

OBJECTIVE

Heart rate asymmetry is a phenomenon in which the contribution of heart rate decelerations to short-term heart rate variability is greater than that of accelerations, and the contribution of accelerations to long-term and total variability is greater than that of decelerations. This has been established for short, stationary recordings, so our aim is to do it for long recordings.

APPROACH

In this paper, we analyze heart rate asymmetry in 87 long, 24 h electrocardiogram Holter recordings from healthy people. We show that in the whole recording all types of asymmetry are observable, clear and highly statistically significant. To analyze the local changes of asymmetry in time, we analyzed the recordings by disjoint jumping windows of 300 beats.

MAIN RESULTS

This analysis revealed that the local, averaged measures of all types of asymmetry also demonstrate its presence which is highly statistically significant. Additionally, we introduce in this paper a statistical test for asymmetry in a single long recording, as opposed to the current approach in which whole groups are tested. We do this by introducing the proportion of time spent in asymmetry for each recording and using it in the binomial tests.

SIGNIFICANCE

We found that for all the recordings most of the time is spent in asymmetry.

Cardiac baroreflex hysteresis is one of the determinants of the heart period variability asymmetry

In heart period (HP) variability (HPV) recordings the percentage of negative HP variations tends to be greater than that of positive ones and this pattern is referred to as HPV asymmetry (HPVA). HPVA has been studied in several experimental conditions in healthy and pathological populations, but its origin is unclear. The baroreflex (BR) exhibits an asymmetric behavior as well given that it reacts more importantly to positive than negative arterial pressure (AP) variations. We tested the hypothesis that the BR asymmetry (BRA) is a HPVA determinant over spontaneous fluctuations of HP and systolic AP (SAP). We studied 100 healthy subjects (age from 21 to 70 yr, 54 men) comprising 20 subjects in each age decade. Electrocardiogram and noninvasive AP were recorded for 15 min at rest in supine position (REST) and during active standing (STAND). The HPVA was evaluated via Porta's index and Guzik's index, while the BRA was assessed as the difference, and normalized difference, between BR sensitivities computed over positive and negative SAP variations via the sequence method applied to HP and SAP variability. HPVA significantly increased during STAND and decreased progressively with age. BRA was not significantly detected both at REST and during STAND. However, we found a significant positive association between BRA and HPVA markers during STAND persisting even within the age groups. This study supports the use of HPVA indexes as descriptors of BRA and identified a challenge soliciting the BR response like STAND to maximize the association between HPVA and BRA markers.

Heart rate variability categories of fluctuation amplitude and complexity: diagnostic markers of fetal development and its disturbances

OBJECTIVE

In fetal diagnosis the myriad and diversity of heart rate variability (HRV) indices prevents a comparable routine evaluation of disturbances in fetal development and well-being. The work aims at the extraction of a small set of HRV key indices that could help to establish a universal, overarching tool to screen for any disturbance.

APPROACH

HRV indices were organized in categories of short-term (prefix s) and long-term (prefix l) amplitude fluctuations (AMP), complexity (COMP), and patterns (PATTERN) and common representatives for each category were extracted. This procedure was done with respect to the diagnostic value in the evaluation of the maturation age throughout the second and complete third trimester of pregnancy as well as to potential differences associated with maternal life-style factors (physical exercise, smoking), nutrient intervention (docosahexaenoic acid (DHA) supplementation), and complications of pregnancy (gestational diabetes mellitus (GDM), intra-uterine growth restriction (IUGR)).

MAIN RESULTS

We found a comprehensive minimal set that includes [lAMP: short term variation (STV), initially introduced in cardiotocography, sAMP: heart rate increase across one interbeat interval of phase rectified averaged signal - acceleration capacity (ACst1), lCOMP: scale 4 multi-scale entropy (MSE4), PATTERN: skewness] for the maturation age prediction, and partly overlapping [lAMP: STV, sAMP: ACst1, sCOMP: Lempel Ziv complexity (LZC)] for the discrimination of the deviations.

SIGNIFICANCE

The minimal set of category-based HRV representatives allows for a screening of fetal development and well-being. These results are an important step towards a universal and comparable diagnostic tool for the early identification of developmental disturbances. Novelty & Significance Fetal development and its disturbances have been reported to be associated with a multiplicity of HRV indices. Furthermore, these HRV indices change with maturation. We propose the abstraction of HRV categories defined by short- and long-term fluctuation amplitude, complexity, and pattern indices that cover all relevant aspects of maturational age, behavioral influences and a series of pathological disturbances. The study data are provided by multiple centers. Our approach is an important step towards the goal of a standardized diagnostic tool for early identification of fetal developmental disturbances with respect to the reduction of serious complications in the later life.

Visibility graph analysis of temporal irreversibility in sleep electroencephalograms

The study of sleep has continued to garner increased attention. However, most studies assume stationarity of sleep electroencephalogram (EEG) signals, whereas they are typically nonlinear and nonstationary. Little work has focused on the time irreversibility of sleep EEG signals. Hence, the aim of this work is to reveal the temporally irreversible structures of rapid-eye-movement (REM) and non-REM sleep using a visibility algorithm, which is robust to nonstationarity and finite-size effect. Results show that the temporal structure of non-REM sleep is more irreversible than that of REM sleep. The degree of irreversibility is highest in slow-wave sleep. Moreover, statistical analysis suggests that aging is the major factor that affects the irreversibility of sleep signals, while gender and body mass index contribute insignificantly. The dominant role of slow oscillations on the irreversible structures of the sleep signals is also indicated.

Cellular Phone Irradiation of the Head Affects Heart Rate Variability Depending on Inspiration/Expiration Ratio

BACKGROUND

Mobile phones may have harmful health effects and clinical examinations report ambiguous results of exposure concerning neurophysiological and cardiovascular actions.

MATERIALS AND METHODS

This study investigated heart rate asymmetry (HRA) and heart rate variability (HRV) parameters with 1:2 and 1:1 metronome-paced inspiration/expiration ratios during short-term 1,800MHz GSM cellular phone exposure in 20 healthy volunteers.

RESULTS

Significant HRA changes by Porta and Guzik indices were not found on exposure compared to sham exposure. Time-domain HRV parameters on exposure showed significant differences at 1:1 paced, but not at 1:2 paced breathing compared to sham exposure. A mild post-exposure effect was observed regarding root mean square of successive RR-differences.

CONCLUSION

The findings reflect persisting acute effects of GSM handset emission on the autonomic nervous system. Exploring its influences on health status and survival needs further studies. Symmetrical breathing can be used as a sensitizing factor in other HRV/HRA analysis studies.