Increased cardiorespiratory coordination in preeclampsia.

Preeclampsia is one of the main sources of morbidity in pregnancy with a high mortality rate without a known ultimate cause. Using a corpus including 927 measurements of pregnant women with and without different hypertonic diseases at multiple stages of pregnancy, we utilised a new approach to analyse cardiorespiratory coordination. Since the recording quality of respiratory effort was limited due to a high signal to noise ratio, we applied an ECG derived respiration approach to create an ersatz respiratory signal. After applying the few available recordings with a sufficiently high quality of the respiratory signal to validate the substitute, coordigrams were calculated and quantified by utilising an epsilon method. We showed significant (p < 0.05) differences in the coordination in a matched (BMI, age, gestational week) comparison of preeclamptic and healthy subjects. Hopefully future applications of and improvements on these methods are able to create a fast and convenient prediction methodology to reduce the impact of this disease as well as help in the determination of its underlying cause.

Modulations of Heart Rate, ECG, and Cardio-Respiratory Coupling Observed in Polysomnography.

The cardiac component of cardio-respiratory polysomnography is covered by ECG and heart rate recordings. However, their evaluation is often underrepresented in summarizing reports. As complements to EEG, EOG, and EMG, these signals provide diagnostic information for autonomic nervous activity during sleep. This review presents major methodological developments in sleep research regarding heart rate, ECG, and cardio-respiratory couplings in a chronological (historical) sequence. It presents physiological and pathophysiological insights related to sleep medicine obtained by new technical developments. Recorded nocturnal ECG facilitates conventional heart rate variability (HRV) analysis, studies of cyclical variations of heart rate, and analysis of ECG waveform. In healthy adults, the autonomous nervous system is regulated in totally different ways during wakefulness, slow-wave sleep, and REM sleep. Analysis of beat-to-beat heart-rate variations with statistical methods enables us to estimate sleep stages based on the differences in autonomic nervous system regulation. Furthermore, up to some degree, it is possible to track transitions from wakefulness to sleep by analysis of heart-rate variations. ECG and heart rate analysis allow assessment of selected sleep disorders as well. Sleep disordered breathing can be detected reliably by studying cyclical variation of heart rate combined with respiration-modulated changes in ECG morphology (amplitude of R wave and T wave).

Alpha-wave frequency characteristics in health and insomnia during sleep.

Appearances of alpha waves in the sleep electrencephalogram indicate physiological, brief states of awakening that lie in between wakefulness and sleep. These microstates may also cause the loss in sleep quality experienced by individuals suffering from insomnia. To distinguish such pathological awakenings from physiological ones, differences in alpha-wave characteristics between transient awakening and wakefulness observed before the onset of sleep were studied. In polysomnographic datasets of sleep-healthy participants (n = 18) and patients with insomnia (n = 10), alpha waves were extracted from the relaxed, wake state before sleep onset, wake after sleep-onset periods and arousals of sleep. In these, alpha frequency and variability were determined as the median and standard deviation of inverse peak-to-peak intervals. Before sleep onset, patients with insomnia showed a decreased alpha variability compared with healthy participants (P < 0.05). After sleep onset, both groups showed patterns of decreased alpha frequency that was lower for wake after sleep-onset periods of shorter duration. For patients with insomnia, alpha variability increased for short wake after sleep-onset periods. Major differences between the two groups were encountered during arousal. In particular, the alpha frequency in patients with insomnia rebounded to wake levels, while the frequency in healthy participants remained at the reduced level of short wake after sleep-onset periods. Reductions in alpha frequency during wake after sleep-onset periods may be related to the microstate between sleep and wakefulness that was described for such brief awakenings. Reduced alpha variability before sleep may indicate a dysfunction of the alpha generation mechanism in insomnia. Alpha characteristics may also prove valuable in the study of other sleep and attention disorders.

Quantifying the causal strength of multivariate cardiovascular couplings with momentary information transfer.

This article studies a recently introduced information-theoretic approach to detect and quantify the causal couplings in a complex cardiovascular system. In the first step a causal algorithm detects the coupling delays and in the second step the causal strength of each coupling mechanism is quantified using the recently introduced momentary information transfer. As an example, the method is applied to time series of respiration, systolic and diastolic blood pressure, and heart rate of pregnant healthy women and women suffering from pre-eclampsia. A possible explanation for the influence of heart rate on systolic blood pressure is found and some differences between healthy women and patients are discussed.

Sleep apnea-hypopnea quantification by cardiovascular data analysis.

Sleep disorders are a major risk factor for cardiovascular diseases. Sleep apnea is the most common sleep disturbance and its detection relies on a polysomnography, i.e., a combination of several medical examinations performed during a monitored sleep night. In order to detect occurrences of sleep apnea without the need of combined recordings, we focus our efforts on extracting a quantifier related to the events of sleep apnea from a cardiovascular time series, namely systolic blood pressure (SBP). Physiologic time series are generally highly nonstationary and entrap the application of conventional tools that require a stationary condition. In our study, data nonstationarities are uncovered by a segmentation procedure which splits the signal into stationary patches, providing local quantities such as mean and variance of the SBP signal in each stationary patch, as well as its duration L. We analysed the data of 26 apneic diagnosed individuals, divided into hypertensive and normotensive groups, and compared the results with those of a control group. From the segmentation procedure, we identified that the average duration , as well as the average variance <σ2>, are correlated to the apnea-hypoapnea index (AHI), previously obtained by polysomnographic exams. Moreover, our results unveil an oscillatory pattern in apneic subjects, whose amplitude S* is also correlated with AHI. All these quantities allow to separate apneic individuals, with an accuracy of at least 79%. Therefore, they provide alternative criteria to detect sleep apnea based on a single time series, the systolic blood pressure.

Robust fetal ECG extraction and detection from abdominal leads.

The fetal ECG derived from abdominal leads provides an alternative to standard means of fetal monitoring. Furthermore, it permits long-term and ambulant recordings, which expands the range diagnostic possibilities for evaluating the fetal health state. However, due to the temporal and spectral overlap of maternal and fetal signals, the usage of abdominal leads imposes the need for elaborated signal processing routines.In this work a modular combination of processing techniques is presented. Its core consists of two maternal ECG estimation techniques, namely the extended Kalman smoother (EKS) and template adaption (TA) in combination with an innovative detection algorithm. Our detection method employs principles of evolutionary computing to detect fetal peaks by considering the periodicity and morphological characteristics of the fetal signal. In a postprocessing phase, single channel detections are combined by means of kernel density estimation and heart rate correction.The described methodology was presented during the Computing in Cardiology Challenge 2013. The entry was the winner of the closed-source events with average scores for events 4/5 with 15.1/3.32 (TA) and 69.5/4.58 (EKS) on training set-A and 20.4/4.57 (TA) and 219/7.69 (EKS) on test set-B, respectively. Using our own clinical data (24 subjects each 20 min recordings) and statistical measures beyond the Challenge's scoring system, we further validated the proposed method. For our clinical data we obtained an average detection rate of 82.8% (TA) and 83.4% (EKS). The achieved results show that the proposed methods are able produce reliable fetal heart rate estimates from a restricted number of abdominal leads.

Cardio-respiratory coordination increases during sleep apnea.

Cardiovascular diseases are the main source of morbidity and mortality in the United States with costs of more than $170 billion. Repetitive respiratory disorders during sleep are assumed to be a major cause of these diseases. Therefore, the understanding of the cardio-respiratory regulation during these events is of high public interest. One of the governing mechanisms is the mutual influence of the cardiac and respiratory oscillations on their respective onsets, the cardio-respiratory coordination (CRC). We analyze this mechanism based on nocturnal measurements of 27 males suffering from obstructive sleep apnea syndrome. Here we find, by using an advanced analysis technique, the cardiogram, not only that the occurrence of CRC is significantly more frequent during respiratory sleep disturbances than in normal respiration (p-value<10(-51)) but also more frequent after these events (p-value<10(-15)). Especially, the latter finding contradicts the common assumption that spontaneous CRC can only be observed in epochs of relaxed conditions, while our newly discovered epochs of CRC after disturbances are characterized by high autonomic stress. Our findings on the connection between CRC and the appearance of sleep-disordered events require a substantial extension of the current understanding of obstructive sleep apneas and hypopneas.

Synchronisation and coupling analysis: applied cardiovascular physics in sleep medicine.

Sleep is a physiological process with an internal program of a number of well defined sleep stages and intermediate wakefulness periods. The sleep stages modulate the autonomous nervous system and thereby the sleep stages are accompanied by different regulation regimes for the cardiovascular and respiratory system. The differences in regulation can be distinguished by new techniques of cardiovascular physics. The number of patients suffering from sleep disorders increases unproportionally with the increase of the human population and aging, leading to very high expenses in the public health system. Therefore, the challenge of cardiovascular physics is to develop highly-sophisticated methods which are able to, on the one hand, supplement and replace expensive medical devices and, on the other hand, improve the medical diagnostics with decreasing the patient's risk. Methods of cardiovascular physics are used to analyze heart rate, blood pressure and respiration to detect changes of the autonomous nervous system in different diseases. Data driven modeling analysis, synchronization and coupling analysis and their applications to biosignals in healthy subjects and patients with different sleep disorders are presented. Newly derived methods of cardiovascular physics can help to find indicators for these health risks.

Estimating coupling directions in the cardiorespiratory system using recurrence properties.

The asymmetry of coupling between complex systems can be studied by conditional probabilities of recurrence, which can be estimated by joint recurrence plots. This approach is applied for the first time on experimental data: time series of the human cardiorespiratory system in order to investigate the couplings between heart rate, mean arterial blood pressure and respiration. We find that the respiratory system couples towards the heart rate, and the heart rate towards the mean arterial blood pressure. However, our analysis could not detect a clear coupling direction between the mean arterial blood pressure and respiration.

Diminished heart beat non-stationarities in congestive heart failure.

Studies on heart rate variability (HRV) have become popular and the possibility of diagnosis based on non-invasive techniques compels us to overcome the difficulties originated on the environmental changes that can affect the signal. We perform a non-parametric segmentation which consists of locating the points where the signal can be split into stationary segments. By finding stationary segments we are able to analyze the size of these segments and evaluate how the signal changes from one segment to another, looking at the statistical moments given in each patch, for example, mean and variance. We analyze HRV data for 15 patients with congestive heart failure (CHF; 11 males, 4 females, age 56±11 years), 18 elderly healthy subjects (EH; 11 males, 7 females, age 50±7 years), and 15 young healthy subjects (YH; 11 females, 4 males, age 31±6 years). Our results confirm higher variance for YH, and EH, while CHF displays diminished variance with p-values <0.01, when compared to the healthy groups, presenting higher HRV in healthy subjects. Moreover, it is possible to distinguish between YH and EH with p < 0.05 through the segmentation outcomes. We found high correlations between the results of segmentation and standard measures of HRV analysis and a connection to results of detrended fluctuation analysis (DFA). The segmentation applied to HRV studies detects aging and pathological conditions effects on the non-stationary behavior of the analyzed groups, promising to contribute in complexity analysis and providing risk stratification measures.

Coupling analysis of transient cardiovascular dynamics.

The analysis of effects from coupling in and between systems is important in data-driven investigations as practiced in many scientific fields. It allows deeper insights into the mechanisms of interaction emerging among individual smaller systems when forming complex systems as in the human circulatory system. For systems featuring various regimes, usually only the epochs before and after a transition between different regimes are analyzed, although relevant information might be hidden within these transitions. Transient behavior of cardiovascular variables may emerge, on the one hand, from the recovery of the system after a severe disturbance or, on the other hand, from adaptive behavior throughout changes of states. It contains important information about the processes involved and the relations between state variables such as heart rate, blood pressure, and respiration. Therefore, we apply an ensemble approach to extend the method of symbolic coupling traces to time-variant coupling analysis. These new ensemble symbolic coupling traces are capable of determining coupling direction, strength, and time offset τ from transient dynamics in multivariate cardiovascular data. We use this method to analyze data recorded during an orthostatic test to reveal a transient structure that cannot be detected by classic methods.

Preserved autonomic regulation in patients undergoing transcatheter aortic valve implantation (TAVI): a prospective, comparative study.

Heart rate and blood pressure variability as well as baroreflex sensitivity (BRS) lead to additional insights on the patients' prognosis after cardiovascular events. The following study was performed to assess the differences in the postoperative recovery of the autonomic regulation after transcatheter aortic valve implantation (TAVI) and surgical aortic valve replacement (SAVR). Fifty-eight consecutive patients were enrolled in a prospective study; 24 underwent TAVI and 34 SAVR. BRS was calculated according to the Dual Sequence Method, heart rate variability (HRV) was evaluated using standard linear as well as nonlinear parameters. HRV and BRS parameters were reduced after surgery in patients with SAVR only (meanNN: p<0.001, sdNN: p<0.05, Shannon: p<0.01, BRS: p<0.01), while these indexes were preserved in patients after TAVI. Simultaneously, an increased complexity of blood pressure (BP) in SAVR patients (fwShannon: p<0.001, fwRenyi4: p<0.001), but not in TAVI patients was recorded. In this study we were able to demonstrate for the first time that, in contrast to patients undergoing conventional open surgery, there are fewer alterations of the cardiovascular autonomic system in patients with TAVI.

Cardiovascular regulation in different sleep stages in the obstructive sleep apnea syndrome.

Heart rate and blood pressure variability analysis as well as baroreflex sensitivity have been proven to be powerful tools for the assessment of autonomic control in clinical practice. Their ability to detect systematic changes caused by different states, diseases and treatments shall be shown for sleep disorders. Therefore, we consider 18 normotensive and 10 hypertensive patients suffering from obstructive sleep apnea syndrome (OSAS) before and after a three-month continuous positive airway pressure (CPAP) therapy. Additionally, an age and sex matched control group of 10 healthy subjects is examined. Linear and nonlinear parameters of heart rate and blood pressure fluctuation as well as the baroreflex sensitivity are used to answer the question whether there are differences in cardiovascular regulation between the different sleep stages and groups. Moreover, the therapeutic effect of CPAP therapy in OSAS patients shall be investigated. Kruskal-Wallis tests between the sleep stages for each group show significant differences in the very low spectral component of heart rate (VLF/P: 0.0033-0.04 Hz, p<0.01) which indicates differences in metabolic activity during the night. Furthermore, the decrease of Shannon entropy of word distribution as a parameter of systolic blood pressure during non-REM sleep reflects the local dominance of the vagal system (p<0.05). The increased sympathetic activation of the patients leads to clear differences of cardiovascular regulation in different sleep stages between controls and patients. We found a significant reduction of baroreflex sensitivity in slow wave sleep in the OSAS patients (Mann-Whitney test, p<0.05) compared to controls, which disappeared after three months of CPAP therapy. Hence, our results demonstrate the ability of cardiovascular analyzes to separate between healthy and pathological regulation as well as between different severities of OSAS in this retrospective study.

Cardiovascular and respiratory regulation during sleep in patients with sleep apnea with and without hypertension.

Sleep is a physiological process with an internal program of a number of well defined sleep stages and intermediate wakefulness periods. The sleep stages do modulate the autonomous nervous system and thereby the sleep stages are accompanied by different regulation regimes for the cardiovascular and respiratory system. The differences in regulation can be distinguished by new analysis techniques on the recorded signals. In addition to normal sleep regulation some sleep disorders affect the cardiovascular and respiratory regulation. The most prevalent disorder linked to sleep and changes in the autonomous system is obstructive sleep apnea. In patients with obstructive sleep apnea marked short term changes in cardiovascular and respiratory regulation are observed during sleep. These abnormalities in regulation are further differentiated between the sleep stages. For long term changes obstructive sleep apnea is recognized as a major risk factor for arterial hypertension. Treatment of obstructive sleep apnea lowers blood pressure during the night and over time also lowers blood pressure during daytime. In this study we investigated 18 patients with sleep apnea and normal blood pressure, 10 patients with sleep apnea and arterial hypertension and 10 normal subjects as controls. Both patient groups were tested with cardiorespiratory polysomnography before and under CPAP therapy. The effects on cardiovascular and respiratory regulation during sleep and daytime are investigated in the three groups.

Cardiovascular and respiratory dynamics in patients with sleep apnea.

Sleep is an active and regulated process with restorative functions for physical and mental conditions. Based on recordings of brain waves and the analysis of characteristic patterns and waveforms it is possible to distinguish wakefulness and five sleep stages. Sleep and the sleep stages modulate autonomous nervous system functions such as body temperature, respiration, blood pressure, and heart rate. Methods of statistical physics are used to analyze heart rate and respiration to detect changes of the autonomous nervous system during sleep. Detrended fluctuation analysis and synchronization analysis and their applications to heart rate and respiration during sleep in healthy subjects and patients with sleep disorders are presented. The observed changes can be used to distinguish sleep stages in healthy subjects as well as to differentiate normal and disturbed sleep on the basis of heart rate and respiration recordings without direct recording of brain waves. Of special interest are the cardiovascular consequences of disturbed sleep because they present a risk factor for cardiovascular disorders such as arterial hypertension, cardiac ischemia, sudden cardiac death, and stroke.

Short-term couplings of the cardiovascular system in pregnant women suffering from pre-eclampsia.

Pre-eclampsia (PE), a serious pregnancy-specific disorder, causes significant neonatal and maternal morbidity and mortality. Recent studies showed that cardiovascular variability parameters as well as the baroreflex sensitivity remarkably improve its early diagnosis. For a better understanding of the dynamical changes caused by PE, in this study the coupling between respiration, systolic and diastolic blood pressure, and heart rate is investigated. Thirteen datasets of healthy pregnant women and 10 of subjects suffering from PE are included. Nonlinear additive autoregressive models with external input are used for a model-based coupling analysis following the idea of Granger causality. To overcome the problem of misdetections of standard methods in systems with a dominant driver, a heuristic ensemble approach is used here. A coupling is assumed to be real when existent in more than 80 per cent of the ensemble members, and otherwise denoted as artefacts. As the main result, we found that the coupling structure between heart rate, systolic blood pressure, diastolic blood pressure and respiration for healthy subjects and PE patients is the same and reliable. As a pathological mechanism, however, a significant increased respiratory influence on the diastolic blood pressure could be found for PE patients (p=0.003). Moreover, the nonlinear form of the respiratory influence on the heart rate is significantly different between the two groups (p=0.002). Interestingly, the influence of systolic blood pressure on the heart rate is not selected, which indicates that the baroreflex sensitivity estimation strongly demands the consideration of causal relationships between heart rate, blood pressure and respiration. Finally, our results point to a potential role of respiration for understanding the pathogenesis of PE.

Is the normal heart rate "chaotic" due to respiration?

The incidence of cardiovascular diseases increases with the growth of the human population and an aging society, leading to very high expenses in the public health system. Therefore, it is challenging to develop sophisticated methods in order to improve medical diagnostics. The question whether the normal heart rate is chaotic or not is an attempt to elucidate the underlying mechanisms of cardiovascular dynamics and therefore a highly controversial topical challenge. In this contribution we demonstrate that linear and nonlinear parameters allow us to separate completely the data sets of the three groups provided for this controversial topic in nonlinear dynamics. The question whether these time series are chaotic or not cannot be answered satisfactorily without investigating the underlying mechanisms leading to them. We give an example of the dominant influence of respiration on heart beat dynamics, which shows that observed fluctuations can be mostly explained by respiratory modulations of heart rate and blood pressure (coefficient of determination: 96%). Therefore, we recommend reformulating the following initial question: "Is the normal heart rate chaotic?" We rather ask the following: "Is the normal heart rate 'chaotic' due to respiration?"

Testing foetal-maternal heart rate synchronization via model-based analyses.

The investigation of foetal reaction to internal and external conditions and stimuli is an important tool in the characterization of the developing neural integration of the foetus. An interesting example of this is the study of the interrelationship between the foetal and the maternal heart rate. Recent studies have shown a certain likelihood of occasional heart rate synchronization between mother and foetus. In the case of respiratory-induced heart rate changes, the comparison with maternal surrogates suggests that the evidence for detected synchronization is largely statistical and does not result from physiological interaction. Rather, they simply reflect a stochastic, temporary stability of two independent oscillators with time-variant frequencies. We reanalysed three datasets from that study for a more local consideration. Epochs of assumed synchronization associated with short-term regulation of the foetal heart rate were selected and compared with synchronization resulting from white noise instead of the foetal signal. Using data-driven modelling analysis, it was possible to identify the consistent influence of the heartbeat duration of maternal beats preceding the foetal beats during epochs of synchronization. These maternal beats occurred approximately one maternal respiratory cycle prior to the affected foetal beat. A similar effect could not be found in the epochs without synchronization. Simulations based on the fitted models led to a higher likelihood of synchronization in the data segments with assumed foetal-maternal interaction than in the segment without such assumed interaction. We conclude that the data-driven model-based analysis can be a useful tool for the identification of synchronization.

Cardiovascular and respiratory dynamics during normal and pathological sleep.

Sleep is an active and regulated process with restorative functions for physical and mental conditions. Based on recordings of brain waves and the analysis of characteristic patterns and waveforms it is possible to distinguish wakefulness and five sleep stages. Sleep and the sleep stages modulate autonomous nervous system functions such as body temperature, respiration, blood pressure, and heart rate. These functions consist of a sympathetic tone usually related to activation and to parasympathetic (or vagal) tone usually related to inhibition. Methods of statistical physics are used to analyze heart rate and respiration to detect changes of the autonomous nervous system during sleep. Detrended fluctuation analysis and synchronization analysis and their applications to heart rate and respiration during sleep in healthy subjects and patients with sleep disorders are presented. The observed changes can be used to distinguish sleep stages in healthy subjects as well as to differentiate normal and disturbed sleep on the basis of heart rate and respiration recordings without direct recording of brain waves. Of special interest are the cardiovascular consequences of disturbed sleep because they present a risk factor for cardiovascular disorders such as arterial hypertension, cardiac ischemia, sudden cardiac death, and stroke. New derived variables can help to find indicators for these health risks.