Alexander Suhrbier

Detection of time-delayed interactions in biosignals using symbolic coupling traces

Directional coupling analysis of bivariate time series is an important subject of current research. In this letter, a method based on symbolic dynamics for the detection of time-delayed coupling is presented. The symbolic coupling traces, defined as the symmetric and diametric traces of the bivariate word distribution, allow for the quantification of coupling and are compared with established methods like mutual information and cross recurrence analysis. The symbolic coupling traces method is applied to model systems and cardiological data which demonstrate its advantages especially for nonstationary data.

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.

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.

Comparison of three methods for beat-to-beat-interval extraction from continuous blood pressure and electrocardiogram with respect to heart rate variability analysis / Vergleich von drei Methoden der Schlag-zu-Schlag-Intervall-Extraktion aus kontinuierlichen Blutdruckverläufen und Elektrokardiogrammen zur Herzratenvariabilitätsanalyse

Abstract In recent years the analysis of heart rate variability (HRV) has become a suitable method for characterizing autonomous cardiovascular regulation. The aim of this study was to investigate the differences in HRV estimated from continuous blood pressure (BP) measurement by different methods in comparison to electrocardiogram (ECG) signals. The beat-to-beat intervals (BBI) were simultaneously extracted from the ECG and blood pressure of 9 cardiac patients (10 min, Colin system, 1000-Hz sampling frequency). For both data types, slope, peak, and correlation detection algorithms were applied. The short-term variability was calculated using concurrent 10-min BP and ECG segments. The root mean square errors in comparison to ECG slope detection were: 1.74 ms for ECG correlation detection; 5.42 ms for ECG peak detection; 5.45 ms for BP slope detection; 5.75 ms for BP correlation detection; and 11.96 ms for BP peak detection. Our results show that the variability obtained with ECG is the most reliable. Moreover, slope detection is superior to peak detection and slightly superior to correlation detection. In particular, for ECG signals with higher frequency characteristics, peak detection often exhibits more artificial variability. Besides measurement noise, respiratory modulation and pulse transit time play an important role in determining BBI. The slope detection method applied to ECG should be preferred, because it is more robust as regards morphological changes in the signals, as well as physiological properties. As the ECG is not recorded in most animal studies, distal pulse wave measurement in combination with correlation or slope detection may be considered an acceptable alternative.

Effect of CPAP therapy on daytime cardiovascular regulations in patients with obstructive sleep apnea

Obstructive sleep apnea (OSA) is a sleep disorder with a high prevalence that causes pathological changes in cardiovascular regulation during the night and also during daytime. We investigated whether the treatment of OSA at night by means of continuous positive airway pressure (CPAP) improves the daytime consequences. Twenty-eight patients with OSA, 18 with arterial hypertension, 10 with normal blood pressure, were investigated at baseline and with three months of CPAP treatment. Ten age and sex matched healthy control subjects were investigated for comparisons. We recorded a resting period with 20min quiet breathing and an exercise stress test during daytime with ECG and blood pressure (Portapres). The bicycle ergometry showed a significant reduction of the diastolic blood pressure at a work load of 50W and 100W (p<0.05 and p<0.01, respectively) and a decrease of the heart rate recovery time after the stress test (p<0.05). These results indicate a reduction of vascular resistance and sympathetic activity during daytime. The coupling analysis of the resting periods by means of symbolic coupling traces approach indicated an effect of the CPAP therapy on the baroreflex reaction in hypertensive patients where influences of the systolic blood pressure on the heart rate changed from pathological patterns to adaptive mechanisms of the normotensive patients (p<0.05).

Investigation of an Automatic Sleep Stage Classification by Means of Multiscorer Hypnogram

OBJECTIVES Scoring sleep visually based on polysomnography is an important but time-consuming element of sleep medicine. Whereas computer software assists human experts in the assignment of sleep stages to polysomnogram epochs, their performance is usually insufficient. This study evaluates the possibility to fully automatize sleep staging considering the reliability of the sleep stages available from human expert sleep scorers. METHODS We obtain features from EEG, ECG and respiratory signals of polysomnograms from ten healthy subjects. Using the sleep stages provided by three human experts, we evaluate the performance of linear discriminant analysis on the entire polysomnogram and only on epochs where the three experts agree in their sleep stage scoring. RESULTS We show that in polysomnogram intervals, to which all three scorers assign the same sleep stage, our algorithm achieves 90% accuracy. This high rate of agreement with the human experts is accomplished with only a small set of three frequency features from the EEG. We increase the performance to 93% by including ECG and respiration features. In contrast, on intervals of ambiguous sleep stage, the sleep stage classification obtained from our algorithm, agrees with the human consensus scorer in approximately 61%. CONCLUSIONS These findings suggest that machine classification is highly consistent with human sleep staging and that error in the algorithms assignments is rather a problem of lack of well-defined criteria for human experts to judge certain polysomnogram epochs than an insufficiency of computational procedures.

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

Abstract 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.

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.

Symbolic coupling traces for causality analysis of cardiovascular control

Directional coupling analysis of time series is an important subject of current research. In this paper, a method based on symbolic dynamics for the detection of time-delayed coupling in biosignals is presented. The symbolic coupling traces, defined as the symmetric and diametric traces of the bivariate word distribution, allow for a more reliable quantification of coupling and are compared with established methods like mutual information and cross recurrence analysis. The symbolic coupling traces method is applied to appropriate model systems and cardiological data which demonstrate its advantages especially for nonstationary and noisy data. Moreover, the method of symbolic coupling traces is used to analyze and quantify time-delayed coupling of cardiovascular measurements during different sleep stages. Significant different regulatory mechanisms are detected not only between the deep sleep and the other sleep stages but also between healthy subjects and patients. The proposed method may help to indicate pathological changes in cardiovascular regulation and also effects of continuous positive airway pressure therapy on the cardiovascular system.

The influence of the spatial separation of control elements on the workload for mobile information systems

Mobile information systems (MIS) are finding their way into private and business every-day activities. There are also increased attempts to establish MIS for on-site activities in industrial facilities. Industrial environments, however, place significantly higher demands on mobile user interfaces than office or home environments. Common interaction styles are often unsuitable for this domain. MIS comprising specialized configurations like wearable systems might overcome current limitations. Wearable systems make it possible to arrange system components in the immediate environment of the users body in order to create an ergonomic and intuitive user interface. However, the use of distributed, body-worn user interfaces, and in particular separation of input and output devices, might increase the workload for the user. This study examines the extent to which the separation of input and output devices affects the workload for wearable MIS. Three interaction styles in two different configurations are investigated with four different measures to determine the workload covering both objective and subjective indicators. This investigation shows that there is no significant increase of workload in general. However, the measurement of the heart rate variability revealed subtle but significant differences between the two configurations, particularly for one interaction style. These findings indicate that physiological measures can provide more detailed and subtle information about additional workload and its source than other measures.