Agnes Schumann

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In this study heart rate variability (HRV) analysis was applied to characterize patients suffering from coronary heart disease (CHD), dilated cardiomyopathy (DCM) and patients who had survived an acute myocardial infarction (MI). On the basis of several HRV parameters, an optimal discrimination between the different kinds of cardiovascular diseases and(More)
Standard parameters of heart rate variability are restricted in measuring linear effects, whereas nonlinear descriptions often suffer from the curse of dimensionality. An approach which might be capable of assessing complex properties is the calculation of entropy measures from normalised periodograms. Two concepts, both based on autoregressive spectral(More)
Assessment of fluctuations in heart rate (HR) following a premature ventricular complex (PVC) is valuable for identifying patients at high risk of sudden cardiac death. We hypothesised that postextrasystolic potentiation is the main determinant of the regulation patterns of blood pressure (BP) and HR following a PVC. Twelve patients with idiopathic dilated(More)
BACKGROUND We tested whether or not heart rate variability (HRV) changes can serve as early signs of ventricular tachycardia (VT) and predict slow and fast VT in patients with an implantable cardioverter defibrillator (ICD). METHODS AND RESULTS We studied the ICD stored 1000 beat-to-beat intervals before the onset of VT (131 episodes) and during a control(More)
Recently, Neural Networks became a popular method in geosciences in the context of pattern recognition problems. They can be used for classification of well logs, for image processing, for anomaly detection and similar problems. In the past, such problems were mainly solved by statistical approaches. However parametric statistical classification methods(More)
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