Bivariate Phase Rectified Signal Averaging Research Articles

Maternal cardiorespiratory coupling: differences between pregnant and nonpregnant women are further amplified by sleep-stage stratification.

Pregnancy complications are associated with abnormal maternal autonomic regulation. Subsequently, thoroughly understanding maternal autonomic regulation during healthy pregnancy may enable the earlier detection of complications, in turn allowing for the improved management thereof. Under healthy autonomic regulation, reciprocal interactions occur between the cardiac and respiratory systems, i.e., cardiorespiratory coupling (CRC). Here, we investigate, for the first time, the differences in CRC between healthy pregnant and nonpregnant women. We apply two algorithms, namely, synchrograms and bivariate phase-rectified signal averaging, to nighttime recordings of ECG and respiratory signals. We find that CRC is present in both groups. Significantly less (P < 0.01) cardiorespiratory synchronization occurs in pregnant women (11% vs. 15% in nonpregnant women). Moreover, there is a smaller response in the heart rate of pregnant women corresponding to respiratory inhalations and exhalations. In addition, we stratified these analyses by sleep stages. As each sleep stage is governed by different autonomic states, this stratification not only amplified some of the differences between groups but also brought out differences that remained hidden when analyzing the full-night recordings. Most notably, the known positive relationship between CRC and deep sleep is less prominent in pregnant women than in their nonpregnant counterparts. The decrease in CRC during healthy pregnancy may be attributable to decreased maternal parasympathetic activity, anatomical changes to the maternal respiratory system, and the increased physiological stress accompanying pregnancy. This work offers novel insight into the physiology of healthy pregnancy and forms part of the base knowledge needed to detect abnormalities in pregnancy.NEW & NOTEWORTHY We compare CRC, i.e., the reciprocal interaction between the cardiac and respiratory systems, between healthy pregnant and nonpregnant women for the first time. Although CRC is present in both groups, CRC is reduced during healthy pregnancy; there is less synchronization between maternal cardiac and respiratory activity and a smaller response in maternal heart rate to respiratory inhalations and exhalations. Stratifying this analysis by sleep stages reveals that differences are most prominent during deep sleep.

The Reconstruction of Causal Networks in Physiology.

We systematically compare strengths and weaknesses of two methods that can be used to quantify causal links between time series: Granger-causality and Bivariate Phase Rectified Signal Averaging (BPRSA). While a statistical test method for Granger-causality has already been established, we show that BPRSA causality can also be probed with existing statistical tests. Our results indicate that more data or stronger interactions are required for the BPRSA method than for the Granger-causality method to detect an existing link. Furthermore, the Granger-causality method can distinguish direct causal links from indirect links as well as links that arise from a common source, while BPRSA cannot. However, in contrast to Granger-causality, BPRSA is suited for the analysis of non-stationary data. We demonstrate the practicability of the Granger-causality method by applying it to polysomnography data from sleep laboratories. An algorithm is presented, which addresses the stationarity condition of Granger-causality by splitting non-stationary data into shorter segments until they pass a stationarity test. We reconstruct causal networks of heart rate, breathing rate, and EEG amplitude from young healthy subjects, elderly healthy subjects, and subjects with obstructive sleep apnea, a condition that leads to disruption of normal respiration during sleep. These networks exhibit differences not only between different sleep stages, but also between young and elderly healthy subjects on the one hand and subjects with sleep apnea on the other hand. Among these differences are 1) weaker interactions in all groups between heart rate, breathing rate and EEG amplitude during deep sleep, compared to light and REM sleep, 2) a stronger causal link from heart rate to breathing rate but disturbances in respiratory sinus arrhythmia (breathing to heart rate coupling) in subjects with sleep apnea, 3) a stronger causal link from EEG amplitude to breathing rate during REM sleep in subjects with sleep apnea. The Granger-causality method, although initially developed for econometric purposes, can provide a quantitative, testable measure for causality in physiological networks.

Interlimb Coordination: A New Order Parameter and a Marker of Fatigue During Quasi-Isometric Exercise?

Although exercise-induced fatigue has been mostly studied from a reductionist and component-dominant approach, some authors have started to test the general predictions of theories of self-organized change during exercises performed until exhaustion. However, little is known about the effects of fatigue on interlimb coordination in quasi-isometric actions. The aim of this study was to investigate the effect of exercise-induced fatigue on upper interlimb coordination during a quasi-isometric exercise performed until exhaustion. In order to do this, we hypothesized an order parameter that governs the interlimb coordination as an interlimb correlation measure. In line with general predictions of theory of phase transitions, we expected that the locally averaged values of the order parameter will increase as the fatigue driven system approaches the point of spontaneous task disengagement. Seven participants performed a quasi-isometric task holding an Olympic bar maintaining an initial elbow flexion of 90 degrees until fatigue induced spontaneous task disengagement. The variability of the elbow angle was recorded through electrogoniometry and the obtained time series were divided into three segments for further analysis. Running correlation function (RCF) and adopted bivariate phase rectified signal averaging (BPRSA) were applied to the corresponding initial (30%) and last (30%) segments of the time series. The results of both analyses showed that the interlimb correlation increased between the initial and the final segments of the performed task. Hence, the hypothesis of the research was supported by evidence. The enhancement of the correlation in the last part means a less flexible coordination among limbs. Our results also show that the high magnitude correlation (%RCF > 0.8) and the %Range (END-BEG) may prove to be useful markers to detect the effects of effort accumulation on interlimb coordination. These results may provide information about the loss of adaptability during exercises performed until exhaustion. Finally, we briefly discuss the hypothesis of the inhibitory percolation process being the general explanation of the spontaneous task disengagement phenomenon.

Analysis of the fetal cardio-electrohysterographic coupling at the third trimester of gestation in healthy women by Bivariate Phase-Rectified Signal Averaging.

IntroductionThe fetal cardio-electrohysterographic coupling (FCEC) is defined as the influence of the uterine electrical activity on fetal heart rate. FCEC has been mainly evaluated by visual analysis of cardiotocographic data during labor; however, this physiological phenomenon is poorly explored during the antenatal period. Here we propose an approach known as Bivariate Phase-Rectified Signal Averaging analysis (BPRSA) to assess such FCEC in the late third trimester of low-risk pregnancies. We hypothesized that BPRSA is a more reliable measure of FCEC than visual analysis and conventional measures such as cross-correlation, coherence, and cross-sample entropy. Additionally, by using BPRSA it is possible to detect FCEC even from the third trimester of pregnancy.Material and methodsHealthy pregnant women in the last third trimester of pregnancy (36.6 ± 1.8 gestational weeks) without any clinical manifestation of labor were enrolled in the Maternal and Childhood Research Center (CIMIGen), Mexico City (n = 37). Ten minutes of maternal electrohysterogram (EHG) and fetal heart rate (FHR) data were collected by a transabdominal non-invasive device. The FCEC was quantified by the coefficient of coherence, the maximum normalized cross-correlation, and the cross-sample entropy obtained either from the EHG and FHR raw signals or from the corresponding BPRSA graphs.ResultsWe found that by using BPRSA, the FCEC was detected in 92% cases (34/37) compared to 48% cases (18/37) using the coefficient of coherence between the EHG and FHR raw signals. Also, BPRSA indicated FCEC in 82% cases (30/37) compared to 30% cases (11/37) using the maximum normalized cross-correlation. By comparing the analyses, the BPRSA evidenced higher FCEC in comparison to the coupling estimated from the raw EHG and FHR signals.ConclusionsOur results support the consideration that in the third trimester of pregnancy, the fetal heart rate is also influenced by uterine activity despite the emerging manifestation of this activity before labor. To quantify FCEC, the BPRSA can be applied to FHR and EHG transabdominal signals acquired in the third trimester of pregnancy.

Fetal heart rate variability responsiveness to maternal stress, non-invasively detected from maternal transabdominal ECG.

Prenatal stress (PS) during pregnancy affects in utero- and postnatal child brain-development. Key systems affected are the hypothalamic-pituitary-adrenal axis and the autonomic nervous system (ANS). Maternal- and fetal ANS activity can be gauged non-invasively from transabdominal electrocardiogram (taECG). We propose a novel approach to assess couplings between maternal (mHR) and fetal heart rate (fHR) as a new biomarker for PS based on bivariate phase-rectified signal averaging (BPRSA). We hypothesized that PS exerts lasting impact on fHR. Prospective case-control study matched for maternal age, parity, and gestational age during the third trimester using the Cohen Perceived Stress Scale (PSS-10) questionnaire with PSS-10 over or equal 19 classified as stress group (SG). Women with PSS-10 < 19 served as control group (CG). Fetal electrocardiograms were recorded by a taECG. Coupling between mHR and fHR was analyzed by BPRSA resulting in fetal stress index (FSI). Maternal hair cortisol, a memory of chronic stress exposure for 2-3months, was measured at birth. 538/1500 pregnant women returned the questionnaire, 55/538 (10.2%) mother-child pairs formed SG and were matched with 55/449 (12.2%) consecutive patients as CG. Maternal hair cortisol was 86.6 (48.0-169.2) versus 53.0 (34.4-105.9) pg/mg (p = 0.029). At 36 + 5weeks, FSI was significantly higher in fetuses of stressed mothers when compared to controls [0.43 (0.18-0.85) versus 0.00 (- 0.49-0.18), p < 0.001]. Prenatal maternal stress affects the coupling between maternal and fetal heart rate detectable non-invasively a month prior to birth. Lasting effects on neurodevelopment of affected offspring should be studied. Clinical trial registration: NCT03389178.

Evaluation of Methods to Characterize the Change of the Respiratory Sinus Arrhythmia with Age in Sleep Apnea Patients.

The High Frequency (HF) band of the power spectrum of the Heart Rate Variability (HRV) is widely accepted to contain information related to the respiration. However, it is known that this often results in misleading estimations of the strength of the Respiratory Sinus Arrhythmia (RSA). In this paper, different approaches to characterize the change of the RSA with age, combining HRV and respiratory signals, are studied. These approaches are the bandwidths in the power spectral density estimations, bivariate phase rectified signal averaging, information dynamics, a time-frequency representation, and a heart rate decomposition based on subspace projections. They were applied to a dataset of sleep apnea patients, specifically to periods without apneas and during NREM sleep. Each estimate reflected a different relationship between RSA and age, suggesting that they all capture the cardiorespiratory information in a different way. The comparison of the estimates indicates that the approaches based on the extraction of respiratory information from HRV provide a better characterization of the age-dependent degradation of the RSA.

Estimation of baroreflex sensitivity by the bivariate phase rectified signal averaging method: a comparison with the phenylephrine method

Objectives: A novel technique to assess spontaneous baroreflex sensitivity (BRS) by bivariate phase-rectified signal averaging (PRSA-BRS) has been recently proposed and its independent prognostic power demonstrated. This method, however, has never been compared with the phenyleprine test (Phe-BRS), commonly regarded as the reference method in clinical and research applications. Approach: In 192 heart failure (HF) and 41 post-myocardial infarction (post-MI) patients we compared PRSA-BRS with Phe-BRS, assessing both association and agreement. Main results: Phe-BRS and PRSA-BRS were (mean ± SD) 4.8 ± 5.0 (range: −3.8,25.0) and 1.2 ± 1.5 (−2.1,6.9) ms mmHg−1 in HF (p < 0.0001), and 5.0 ± 3.8 (−1.2,12.5) and 0.8 ± 1.7 (−2.0,6.9) ms mmHg−1 in post-MI patients (p = 0.001). Moderate association was observed (r = 0.53, p < 0.0001 and r = 0.43, p = 0.004 in HF and post-MI, respectively). The vast majority (86% in HF and 90% in post-MI) of PRSA-BRS measurements were smaller than corresponding Phe-BRS values. The difference between PRSA-BRS and Phe-BRS was strongly dependent on the magnitude of BRS, with a trend towards more negative differences as BRS increased. Negative PRSA-BRS values were observed in 15% of HF and in 37% of post-MI patients, whereas negative Phe-BRS values were observed in 8% of HF and 5% of post-MI patients. Significance: Although the association with Phe-BRS suggests that PRSA-BRS contains relevant information about cardiac autonomic control and reflects the strength of the baroreceptor-heart rate reflex, the marked disagreement between the two measurements indicates that PRSA-BRS measurements cannot be taken as estimates of BRS. Many factors may account for the observed lack of agreement: the different physiological conditions under which Phe-BRS and PRSA-BRS are measured, the inclusion of non-baroreflex mediated components of RR-intervals in PRSA-BRS and some computational aspects related to the normalization of PRSA-BRS values.

Feasibility study for the assessment of cardio-respiratory coupling in newborn infants.

Cardio Respiratory Coupling (CRC) plays a key role during infant development. Nonetheless, mechanisms underlying it are still mostly unexplained and tools to assess it are often inadequate to understand its functioning. This study aims to evaluate the feasibility of CRC activity detection and quantification analyzing ECG and respiration of newborn healthy subjects. Cross-spectral analysis (coherence) and a novel application of a nonlinear method (Bivariate Phase Rectified Signal Averaging) were applied on 10 minutes recording from 4 subjects. Our preliminary results show that these methods can provide significant information about the occurrence and the strength of CRC, opening interesting perspectives in the evaluation of cardiorespiratory pathologies in newborn infants. In particular, the observed dynamic behavior appears stable and centered around one single frequency in Quiet Sleep, while being more variable and less consistent in Active Sleep.

Abstract 17230: Respiratory Sinus Arrhythmia Quantified from Standard ECG for Risk Stratification of Post-Infarction Patients

Objectives: Respiratory sinus arrhythmia (RSA) reflects modulation of the sinoatrial node discharge frequency by the autonomic nervous system. Impaired autonomic function is associated with adverse outcome in cardiac patients. We developed a method for calculating RSA from standard ECG recordings and investigated its association with mortality in survivors of acute myocardial infarction. Methods: Consecutive patients (n=941, mean age 61 years, 19% female) presenting with acute myocardial infarction and sinus rhythm were enrolled between May 2000 and March 2005 and followed up until August 2010. The main study outcome was 5-year all-cause mortality. Patients underwent 30-minute ECG recordings. Auxiliary respiratory muscle activity derived from high pass-filtered ECG signal was used to define respiratory phase. The influence of expiration on RR intervals (RRI) was assessed by bivariate phase-rectified signal averaging (PRSA), and RSA PRSA was quantified by Haar wavelet analysis. RSA PRSA ≤0 was defined as abnormal. Results: During the follow-up, 72 patients died. Five-year mortality rates in patients with normal and abnormal RSA PRSA were 4% and 14%, respectively. Under univariable analysis, RSA PRSA was a significant predictor of death (p&lt;0.001), as were GRACE score (p&lt;0.001), LVEF (p&lt;0.001), and the presence of diabetes mellitus (p&lt;0.001). Under multivariable analysis, RSA PRSA , GRACE score, LVEF, and diabetes mellitus were independently and significantly associated with outcome. Conclusions: Respiratory sinus arrhythmia, quantified by bivariate PRSA from standard ECG recordings, is an independent predictor of mortality risk in post-infarction patients.

Assessment of coupling between trans-abdominally acquired fetal ECG and uterine activity by bivariate phase-rectified signal averaging analysis.

Couplings between uterine contractions (UC) and fetal heart rate (fHR) provide important information on fetal condition during labor. At present, couplings between UC and fHR are assessed by visual analysis and interpretation of cardiotocography. The application of computerized approaches is restricted due to the non-stationarity of the signal, missing data and noise, typical for fHR. Herein, we propose a novel approach to assess couplings between UC and fHR, based on a signal-processing algorithm termed bivariate phase-rectified signal averaging (BPRSA).MethodsElectrohysterogram (EHG) and fetal electrocardiogram (fECG) were recorded non-invasively by a trans-abdominal device in 73 women at term with uneventful singleton pregnancy during the first stage of labor. Coupling between UC and fHR was analyzed by BPRSA and by conventional cross power spectral density analysis (CPSD). For both methods, degree of coupling was assessed by the maximum coefficient of coherence (CPRSA and CRAW, respectively) in the UC frequency domain. Coherence values greater than 0.50 were consider significant. CPRSA and CRAW were compared by Wilcoxon test.ResultsAt visual inspection BPRSA analysis identified coupled periodicities in 86.3% (63/73) of the cases. 11/73 (15%) cases were excluded from further analysis because no 30 minutes of fECG recording without signal loss was available for spectral analysis. Significant coupling was found in 90.3% (56/62) of the cases analyzed by BPRSA, and in 24.2% (15/62) of the cases analyzed by CPSD, respectively. The difference between median value of CPRSA and CRAW was highly significant (0.79 [IQR 0.69–0.90] and 0.29 [IQR 0.17–0.47], respectively; p<0.0001).ConclusionBPRSA is a novel computer-based approach that can be reliably applied to trans-abdominally acquired EHG-fECG. It allows the assessment of correlations between UC and fHR patterns in the majority of labors, overcoming the limitations of non-stationarity and artifacts. Compared to standard techniques of cross-correlations, such as CPSD, BPRSA is significantly superior.

Bivariate phase-rectified signal averaging for assessment of spontaneous baroreflex sensitivity: pilot study of the technology

Background Assessment of spontaneous baroreflex sensitivity (BRS), an index of autonomic function, poses practical challenges. In this pilot study, we propose a novel technique for assessment of spontaneous BRS based on bivariate phase-rectified signal averaging (PRSA). This is an extension of the monovariate PRSA technology used for calculation of deceleration capacity. Methods A prospective, observational study was conducted in a training cohort of 146 patients with heart failure (New York Heart Association class 2.7 ± 0.8, left ventricular ejection fraction 23.6% ± 9.0%) presenting with sinus rhythm. In all patients, 10-minute recordings of ECG and arterial and blood pressure were obtained in the supine resting position. The algorithm for BRS assessment based on bivariate PRSA (BRS PRSA) included (1) identification of heartbeat intervals occurring at the time of systolic pressure increases, (2) selection of heartbeat adjacent interval sections, (3) alignment and (4) averaging of these segments, and (5) quantification of the average heart beat interval change by Haar wavelet analysis. Primary end point was death of any cause. During mean follow-up of 2.7 ± 1.1 years, 42 patients (28.8%) died. Results BRS PRSA was significantly associated with the primary end point (3.7 ± 5.3 ms vs −0.33 ± 6.6 ms in survivors and nonsurvivors, respectively). BRS PRSA yielded an area under the receiver operating characteristics curve of 69.8% (95% confidence interval, 59.9-79.7), which was comparable to the area under the curve of left ventricular ejection fraction (70.4%; 95% confidence interval, 61.3-79.5). Using the optimum dichotomy for BRS PRSA of 1.14 milliseconds, 52 (36%) patients had an abnormal BRS PRSA. The 3-year mortality risk of these patients was 45.3% compared to 19.0% in patients with normal BRS PRSA. On multivariate analysis, abnormal BRS PRSA was an independent risk factor from left ventricular ejection fraction ≤ 30% and New York Heart Association class > II. Conclusion BRS PRSA is an independent and strong predictor of mortality in patients with heart failure. Prospective validation and comparisons with standard measures of BRS are needed.

Bivariate phase-rectified signal averaging—a novel technique for cross-correlation analysis in noisy nonstationary signals

Signals generated by biologic systems are characterized by a high degree of nonstationarities and noise. Phase-rectified signal averaging (PRSA) was shown to be superior to conventional methods in detection of periodicities in biologic signals. Bivariate phase-rectified signal averaging (BPRSA) is an extension of the PRSA-method for analysis of interrelationships between 2 synchronously recorded biologic signals. Here, we review the methodology of the technique and demonstrate its performance in simulated data. As application to biologic data, we use BPRSA to analyze synchronously recorded time series of systolic arterial blood pressure, RR intervals, and respiratory activity.

Bivariate phase-rectified signal averaging

Phase-Rectified Signal Averaging (PRSA) was shown to be a powerful tool for the study of quasi-periodic oscillations and nonlinear effects in non-stationary signals. Here we present a bivariate PRSA technique for the study of the inter-relationship between two simultaneous data recordings. Its performance is compared with traditional cross-correlation analysis, which, however, does not work well for non-stationary data and cannot distinguish the coupling directions in complex nonlinear situations. We show that bivariate PRSA allows the analysis of events in one signal when the other signal is in a certain phase or state; it is stable in the presence of noise and impassible to non-stationarities.