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Niels Wessel

Publications and source records attributed to Niels Wessel.

At least 19 recordsLinked to original sources
PubMed2006

Scaling characteristics of heart rate time series before the onset of ventricular tachycardia.

Ventricular tachycardia (VT) provokes sudden cardiac death (SCD), which is a major cause of mortality in developed countries. Implantable cardioverter-defibrillators (ICDs) are an efficient therapy for SCD prevention. In this study we analyze heart rate variability (HRV) in data stored by ICDs. In 29 patients exhibiting VT episodes, the last 1000 normal beat-to-beat intervals are analyzed and compared to an individually acquired control time series (CON). HRV analysis is performed with standard parameters of time and frequency domain as suggested by the HRV Task Force. For scaling analyses of heart rate time series, the fractal dimension is analysed, applying Higuchi's algorithm (HFD). Furthermore, detrended fluctuation analysis (DFA) is performed. None of the standard HRV parameters shows significant differences between CON and VT. Before the onset of VT, the scaling characteristics by means of HFD and DFA are significantly changed. In conclusion, scaling analysis reveals changes in autonomic heart rate modulation preceding VT.

Algorithms↗
PubMed2006

Large-scale dimension densities for heart rate variability analysis.

In this work, we reanalyze the heart rate variability (HRV) data from the 2002 Computers in Cardiology (CiC) Challenge using the concept of large-scale dimension densities and additionally apply this technique to data of healthy persons and of patients with cardiac diseases. The large-scale dimension density (LASDID) is estimated from the time series using a normalized Grassberger-Procaccia algorithm, which leads to a suitable correction of systematic errors produced by boundary effects in the rather large scales of a system. This way, it is possible to analyze rather short, nonstationary, and unfiltered data, such as HRV. Moreover, this method allows us to analyze short parts of the data and to look for differences between day and night. The circadian changes in the dimension density enable us to distinguish almost completely between real data and computer-generated data from the CiC 2002 challenge using only one parameter. In the second part we analyzed the data of 15 patients with atrial fibrillation (AF), 15 patients with congestive heart failure (CHF), 15 elderly healthy subjects (EH), as well as 18 young and healthy persons (YH). With our method we are able to separate completely the AF (rho (mu/ls) = 0.97 +/- 0.02) group from the others and, especially during daytime, the CHF patients show significant differences from the young and elderly healthy volunteers (CHF, 0.65 +/- 0.13; EH, 0.54 +/- 0.05; YH, 0.57 +/- 0.05; p < 0.05 for both comparisons). Moreover, for the CHF patients we find no circadian changes in rho (mu/ls) (day, 0.65 +/- 0.13; night, 0.66 +/- 0.12; n.s.) in contrast to healthy controls (day, 0.54 +/- 0.05; night, 0.61 +/- 0.05; p=0.002). Correlation analysis showed no statistical significant relation between standard HRV and circadian LASDID, demonstrating a possibly independent application of our method for clinical risk stratification.

Atrial Fibrillation↗
PubMed2006

Nonlinear additive autoregressive model-based analysis of short-term heart rate variability.

In this contribution we test the hypothesis that nonlinear additive autoregressive model-based data analysis improves the diagnostic ability based on short-term heart rate variability. For this purpose, a nonlinear regression approach, namely, the maximal correlation method is applied to the data of 37 patients with dilated cardiomyopathy as well as of 37 age- and sex-matched healthy subjects. We find that this approach is a powerful tool in discriminating both groups and promising for further model-based analyses.

Algorithms↗
PubMed2006

Does the C-type natriuretic peptide have prognostic value in chagas disease and other dilated cardiomyopathies?

Atrial natriuretic peptides (ANP) and brain natriuretic peptides (BNP) are powerful neurohormonal indicators of left-ventricular function and prognosis in heart failure (HF). Chagas disease (CD) caused by the protozoan Trypanosoma cruzi remains a major cause of HF in Latin America. We assessed whether the plasma concentration of the third natriuretic peptide, C-type natriuretic peptide (CNP), also has diagnostic and prognostic properties in patients with CD or other dilated cardiomyopathies (DCM). Blood samples were obtained from 66 patients with CD, 50 patients with DCM from other causes, and 30 gender- and age-matched healthy subjects. Patients were subdivided according to the New York Heart Association (NYHA) class. The CNP concentration was determined by radioimmunoassay (Immundiagnostik, Bensheim, Germany). The main duration of follow-up was 31.4 months (range 13 to 54 months); 19 patients had died and 11 patients received a heart transplant. CNP concentrations were only significantly altered in patients with DCM or CD of the NYHA classes III and IV (P < 0.05). The Pearson correlation of echocardiographic data with CNP revealed an association only with the left-ventricular end systolic volume (P = 0.03) in patients with DCM. Furthermore, CNP did not predict mortality or the necessity for heart transplant. Our data are the first to demonstrate the raised levels of the third natriuretic peptide CNP in CD and other DCM. Whereas ANP and BNP have a high predictive value for mortality in both diseases, CNP is without any predictive potency.

Adult↗
PubMed2006

A combined technique for predicting pre-eclampsia: concurrent measurement of uterine perfusion and analysis of heart rate and blood pressure variability.

OBJECTIVE: Pre-eclampsia is a serious complication of pregnancy with high morbidity and mortality and an incidence of 3-5% in all pregnancies. Early prediction is still insufficient in clinical practice. Although most pre-eclamptic patients have pathological uterine perfusion in the second trimester, perfusion disturbance has a positive predictive accuracy (PPA) only of approximately 30%. METHODS: Non-invasive continuous blood pressure recordings were taken simultaneously via a finger cuff for 30 min. Time series of systolic as well as diastolic beat-to-beat pressure values were extracted to analyse heart rate and blood pressure variability and baroreflex sensitivity in 102 second-trimester pregnancies, to assess predictability for pre-eclampsia (n = 16). All women underwent Doppler investigations of the uterine arteries. RESULTS: We identified a combination of three variability and baroreflex parameters to best predict pre-eclampsia several weeks before clinical manifestation. The discriminant function of these three parameters classified patients with later pre-eclampsia with a sensitivity of 87.5%, a specificity of 83.7%, and a PPA of 50.0%. Combined with Doppler investigations of uterine arteries, PPA increased to 71.4%. CONCLUSIONS: This technique of incorporating one-stop clinical assessment of uterine perfusion and variability parameters in the second trimester produces the most effective prediction of pre-eclampsia to date.

Adult↗
PubMed2006

Comparison of three methods for beat-to-beat-interval extraction from continuous blood pressure and electrocardiogram with respect to heart rate variability analysis.

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.

Adult↗
PubMed2006

Normalized correlation dimension for heart rate variability analysis.

In this paper we use the concept of large-scale dimension densities to analyze heart rate variability data. This method uses a normalized Grassberger-Procaccia algorithm and estimates the dimension in the rather large scales of the system. This enables us to analyze very short data. First we re-analyze data from the CIC 2002 challenge and can completely distinguish between real data and computer-generated data using only one parameter. We then analyze unfiltered data for 15 patients with atrial fibrillation (AF), 15 patients with congestive heart failure (CHF), 15 elderly healthy subjects, and 18 young healthy subjects. This method can completely separate the AF group from the other groups and the CHF patients show significant differences compared to the young and elderly healthy volunteers. Furthermore, differences are evident in the dimensionality between day and night for healthy persons, but not for the CHF patients. Finally, the results are compared to standard heart rate variability parameters.

Adult↗
PubMed2005

Correlation dimension analysis of heart rate variability in patients with dilated cardiomyopathy.

A correlation dimension analysis of heart rate variability (HRV) was applied to a group of 55 patients with dilated cardiomyopathy (DCM) and 55 healthy subjects as controls. The 24-h RR time series for each subject was divided into segments of 10,000 beats to determine the correlation dimension (CD) per segment. A study of the influence of the time delay (lag) in the calculation of CD was performed. Good discrimination between both groups (p<0.005) was obtained with lag values of 5 or greater. CD values of DCM patients (8.4+/-1.9) were significantly lower than CD values for controls (9.5+/-1.9). An analysis of CD values of HRV showed that for healthy people, CD night values (10.6+/-1.8) were significant greater than CD day values (9.2+/-1.9), revealing a circadian rhythm. In DCM patients, this circadian rhythm was lost and there were no differences between CD values in day (8.8+/-2.4) and night (8.9+/-2.1).

Adult↗
PubMed2005

Longitudinal analysis of heart rate variability in chronic hypertensive pregnancy.

In the US, it is currently estimated that 3% of pregnant women have chronic hypertension, or more than 100,000 pregnant women each year. The aim of our study was to investigate the adaptation of autonomic control during pregnancy based on heart rate variability analysis and to determine whether chronic hypertension during pregnancy has an impact on this adaptation. Sixteen pregnant women with chronic hypertension (CH group; mean age, 30 years; range, 25-33 years) and 35 healthy pregnant women serving as controls (CON group; mean age, 28 years; range, 24-30 years) were recruited for this longitudinal study. Beginning at the 20th week of pregnancy, the women were monitored every 4th week until delivery. For the analysis of heart rate variability, Portapres signals (200 Hz) were recorded for 30 min under resting conditions. Women in the CH group had significantly elevated blood pressure compared to controls (CON, 111 mmHg [105-132]; CH, 140 mmHg [132-148]; p<0.001). An increased heart rate was found in both groups during the second half of pregnancy. Consequently, decreased heart rate variability was observed, but was more pronounced in the CON group. There was a shift in the frequency bands indicated by an elevation of the low-to-high frequency ratio (LF/HF) in both groups due to a decrease in HF, and thus a significant increase in LFn (LF power in normalized units). However, VLF (power of very low frequency range) increased exclusively in the CON pregnancies. Our data showed no significant difference in heart rate variability between the subjects of the CH and CON groups. Longitudinal variations were detectable in normal pregnancies and also, albeit to a lesser degree, in chronic hypertensive pregnant women. Thus, our data indicate that patients with long-term hypertension are still able to respond to the physiological changes occurring during pregnancy.

Adult↗
PubMed2004

Short-term heart rate turbulence analysis versus variability and baroreceptor sensitivity in patients with dilated cardiomyopathy.

New methods for the analysis of arrhythmias and their hemodynamic consequences have been applied in risk stratification, in particular to patients after myocardial infarction. This study investigates the suitability of short-term heart rate turbulence (HRT) analysis in comparison to heart rate and blood pressure variability as well as baroreceptor sensitivity analyses to characterise the regulatory differences between patients with dilated cardiomyopathy (DCM) and healthy controls. In this study, 30 minutes data of non-invasive continuous blood pressure and ECGs of 37 DCM patients and 167 controls measured under standard resting conditions were analysed. The results show highly significant differences between DCM patients and controls in heart rate and blood pressure variability as well as in baroreceptor sensitivity parameters. Applying a combined heart rate-blood pressure trigger, ventricular premature beats were detected in 24.3% (9) of the DCM patients and 11.3% (19) of the controls. This fact demonstrates the limited applicability of short-term HRT analyses. However, the HRT parameters showed significant differences in this subgroup with ventricular premature beats (turbulence onset: DCM: 1.80+/-2.72, controls: - 4.34+/-3.10, p<0.001; turbulence slope: DCM: 6.75+/-5.50, controls: 21.30+/-17.72, p=0.021). Considering all (including HRT) parameters in the subgroup with ventricular beats, a discrimination rate between DCM patients and controls of 88.0% was obtained (max. 6 parameters). The corresponding value obtained for the total group was 86.3% (without HRT parameters). Comparable classification rates and high correlations between heart rate turbulence and variability and baroreflex parameters point to a more universal applicability of the latter methods.

Journal Article↗
PubMed2004

alpha-Tropomyosin mutations Asp(175)Asn and Glu(180)Gly affect cardiac function in transgenic rats in different ways.

To study the mechanisms by which missense mutations in alpha-tropomyosin cause familial hypertrophic cardiomyopathy, we generated transgenic rats overexpressing alpha-tropomyosin with one of two disease-causing mutations, Asp(175)Asn or Glu(180)Gly, and analyzed phenotypic changes at molecular, morphological, and physiological levels. The transgenic proteins were stably integrated into the sarcomere, as shown by immunohistochemistry using a human-specific anti-alpha-tropomyosin antibody, ARG1. In transgenic rats with either alpha-tropomyosin mutation, molecular markers of cardiac hypertrophy were induced. Ca(2+) sensitivity of cardiac skinned-fiber preparations from animals with mutation Asp(175)Asn, but not Glu(180)Gly, was decreased. Furthermore, elevated frequency and amplitude of spontaneous Ca(2+) waves were detected only in cardiomyocytes from animals with mutation Asp(175)Asn, suggesting an increase in intracellular Ca(2+) concentration compensating for the reduced Ca(2+) sensitivity of isometric force generation. Accordingly, in Langendorff-perfused heart preparations, myocardial contraction and relaxation were accelerated in animals with mutation Asp(175)Asn. The results allow us to propose a hypothesis of the pathogenetic changes caused by alpha-tropomyosin mutation Asp(175)Asn in familial hypertrophic cardiomyopathy on the basis of changes in Ca(2+) handling as a sensitive mechanism to compensate for alterations in sarcomeric structure.

Animals↗
PubMed2004

Predicting thermal displacements in modular tool systems.

In the last decade, there has been an increasing interest in compensating thermally induced errors to improve the manufacturing accuracy of modular tool systems. These modular tool systems are interfaces between spindle and workpiece and consist of several complicatedly formed parts. Their thermal behavior is dominated by nonlinearities, delay and hysteresis effects even in tools with simpler geometry and it is difficult to describe it theoretically. Due to the dominant nonlinear nature of this behavior the so far used linear regression between the temperatures and the displacements is insufficient. Therefore, in this study we test the hypothesis whether we can reliably predict such thermal displacements via nonlinear temperature-displacement regression functions. These functions are estimated first from learning measurements using the alternating conditional expectation (ACE) algorithm and then tested on independent data sets. First, we analyze data that were generated by a finite element spindle model. We find that our approach is a powerful tool to describe the relation between temperatures and displacements for simulated data. Next, we analyze the temperature-displacement relationship in a silent real experimental setup, where the tool system is thermally forced. Again, the ACE algorithm is powerful to estimate the deformation with high precision. The corresponding errors obtained by using the nonlinear regression approach are 10-fold lower in comparison to multiple linear regression analysis. Finally, we investigate the thermal behavior of a modular tool system in a working milling machine and again get promising results. The thermally induced errors can be estimated with 1-2 microm accuracy using this nonlinear regression analysis. Therefore, this approach seems to be very useful for the development of new modular tool systems.

Computer Simulation↗
PubMed2003

Analytical model for a cooperative ballistic deposition in one dimension.

We formulate a model for a cooperative ballistic deposition (CBD) process whereby the incoming particles are correlated with those already adsorbed via attractive force. The strength of the correlation is controlled by a tunable parameter a that interpolates the classical car parking problem at a=0, the ballistic deposition at a=1, and the CBD model at a>1. The effects of the correlation in the CBD model are as follows. The jamming coverage q(a) increases with the strength of attraction a due to an ever-increasing tendency of cluster formation. The system almost reaches the closest packing structure as a-->infinity but never forms a percolating cluster, which is typical of one-dimensional systems. In the large a regime, the mean cluster size k increases as a(1/2). Furthermore, the asymptotic approach towards the closest packing is purely algebraic both with a as q(infinity)-q(a) approximately a(-1/2) and with k as q(infinity)-q(k) approximately k(-1), where q(infinity) approximately 1.

Journal Article↗