arXiv subjects

H. Moelgaard

Publications and source records attributed to H. Moelgaard.

3 recordsLinked to original sources

arXiv2000

Scale Specific and Scale Independent Measures of Heart Rate Variability as Risk Indicators

We study the Heart Rate Variability (HRV) using scale specific variance and scaling exponents as measures of healthy and cardiac impaired individuals. Our results show that the variance and the scaling exponent are uncorrelated. We find that the variance measure at certain scales is well suited to separate healthy subjects from heart patients. However, for cumulative survival probability the scaling exponents outperform the variance measure. Our risk study is based on a database containing recordings from 428 individuals after myocardial infarct (MI) and on database containing 105 healthy subjects and 11 heart patients. The results have been obtained by applying three recently developed methods (DFA - Detrended Fluctuation Analysis, WAV - Multiresolution Wavelet Analysis, and DTS - Detrended Time Series analysis) which are shown to be highly correlated.

physics.med-ph↗

arXiv1998

Discrimination between Healthy and Sick Cardiac Autonomic Nervous System by Detrended Heart Rate Variability Analysis

Multiresolution Wavelet Transform and Detrended Fluctuation Analysis have been recently proven as excellent methods in the analysis of Heart Rate Variability, and in distinguishing between healthy subjects and patients with various dysfunctions of the cardiac nervous system. We argue that it is possible to obtain a distinction between healthy subjects/patients of at least similar quality by, first, detrending the time-series of RR-intervals by subtracting a running average based on a local window with a length of around 32 data points, and then, calculating the standard deviation of the detrended time-series. The results presented here indicate that the analysis can be based on very short time-series of RR-data (7-8 minutes), which is a considerable improvement relative to 24-hours Holter recordings.

chao-dyn↗

arXiv1998

Discrimination of the Healthy and Sick Cardiac Autonomic Nervous System by a New Wavelet Analysis of Heartbeat Intervals

We demonstrate that it is possible to distinguish with a complete certainty between healthy subjects and patients with various dysfunctions of the cardiac nervous system by way of multiresolutional wavelet transform of RR intervals. We repeated the study of Thurner et al on different ensemble of subjects. We show that reconstructed series using a filter which discards wavelet coefficients related with higher scales enables one to classify individuals for which the method otherwise is inconclusive. We suggest a delimiting diagnostic value of the standard deviation of the filtered, reconstructed RR interval time series in the range of $\sim 0.035$ (for the above mentioned filter), below which individuals are at risk.

physics.med-ph↗