Biomedical subjects

Niels Wessel

Publications and source records attributed to Niels Wessel.

22 records · Page 2Linked to original sources

PubMed2002

Potential of feature selection methods in heart rate variability analysis for the classification of different cardiovascular diseases.

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 between the diseases and healthy controls (HC) was derived by feature selection and linear classification. For each task a small favourable subset of a set of 33 potentially interesting HRV measures was selected with the intention of improving the diagnostic value and facilitating the physiological interpretation of HRV analysis. Time- and frequency-domain parameters as well as parameters from non-linear dynamics were included in the analysis. With the expectation that different diseases are characterized by different phenomena, feature selection was applied for each task separately. Using the features optimal for one task to another task can reveal a loss in performance, but it turned out that one specific parameter set (set1: normalized low frequency LF/P and a non-linear variability measure WPSUM13) was applicable for all tasks, where diseased and healthy subjects have to be distinguished, without significant reduction in performance. This set seems to be a general marker for pathologic changes in HRV and might be used for early detection of heart diseases. The classification between different heart diseases requires another parameter set (set2: meanNN and sdaNN, reflecting the steady state behaviour of the heart rate and long and short term SEAR describing the spectral composition). However, the use of set1 for the separation of different kinds of diseases, where set2 is appropriate, led to significant reduction in performance and vice versa. This observation may be important for future developments of HRV measures especially suitable for the assessment of disease severity.

Cardiovascular Diseases↗

PubMed2002

Recurrence-plot-based measures of complexity and their application to heart-rate-variability data.

The knowledge of transitions between regular, laminar or chaotic behaviors is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods that, however, require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart-rate-variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e., chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our measures to the heart-rate-variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias.

Journal Article↗

PubMed2002

Heart rate variability before the onset of ventricular tachycardia: differences between slow and fast arrhythmias.

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 time without VT (74 series) in 63 chronic heart failure ICD patients. Standard HRV parameters as well as two nonlinear parameters, namely 'Polvar10' from symbolic dynamics and the finite time growth rates 'Fitgra9' were calculated. Comparing the control and the VT series, no linear HRV parameter showed a significant difference. The nonlinear parameters detected a significant increase in short phases with low variability before the onset of VT (for time series with less than 10% ectopy, P<0.05). Subdividing VT into fast (cycle length 270 ms) events, we found that the onset of slow VT was characterized by a significant increase in heart rate, whereas fast VT was triggered during decreased heart rates, compared to the control series. CONCLUSIONS: Our data may permit the development of automatic ICD algorithms based on nonlinear dynamic HRV parameters to predict VT before it starts. Furthermore, they may facilitate improved prevention strategies.

Adult↗

PubMed2002

Advanced analysis of spontaneous baroreflex sensitivity, blood pressure and heart rate variability in patients with dilated cardiomyopathy.

Baroreflex sensitivity (BRS) is an important parameter in the classification of patients with reduced left ventricular function. This study aimed at investigating BRS in patients with dilated cardiomyopathy (DCM) and in healthy subjects (controls), as well as comparing the values of BRS parameters with parameters of heart rate variability (HRV) and blood pressure variability (BPV). ECG, continuous blood pressure and respiration curves were recorded for 30 min in 27 DCM patients and 27 control subjects. The Dual Sequence Method (DSM) includes the analysis of spontaneous fluctuations in systolic blood pressure and the corresponding beat-to-beat intervals of heart rate to estimate bradycardic, opposite tachycardic and delayed baroreflex fluctuations. The number of systolic blood pressure/beat-to-beat interval fluctuations in DCM patients was reduced in comparison with controls (DCM patients: male, 154.4+/-93.9 ms/mmHg; female, 93.7+/-40.5 ms/mmHg; controls: male, 245.5+/-112.9 ms/mmHg; female, 150.6+/-55.8 ms/mmHg, P<0.05). The average slope in DCM patients was lower than in controls (DCM, 5.3+/-1.9 ms/mmHg; controls, 8.0+/-5.4 ms/mmHg; P<0.05). Discriminant function analysis showed that, in the synchronous range of the standard sequence method, the DCM and control groups could be discriminated to only 76% accuracy, whereas the DSM gave an improved accuracy of 84%. The combination of six parameters of HRV, BPV and DSM gives an accuracy of classification of 96%, whereas six parameters of HRV and BPV could separate the two groups to only 88% accuracy. Thus the DSM leads to an improved characterization of autonomous regulation in order to differentiate between DCM patients and healthy subjects. BRS in DCM patients is significantly reduced and apparently less effective.

Adult↗