Abstract
We have developed numerical approaches to dynamical analysis of heart rates, measured as interbeat or RR, intervals, based on entropy and fluctuation analyses in a large data base of consecutive Holter monitor recordings. In Part I, we present a RR interval-based classifier that distinguishes normal sinus rhythm (NSR), atrial fibrillation (AF) and sinus rhythm with ectopy with an accuracy of 99%, 81% and 77%respectively, using 10-minute segments. In Part II, we present 2-year mortality estimation based on the entropy calculations. The major finding is that normal dynamics identify a very low risk group. Taken together, these results point to automated analysis of heart rate time series with important clinical applications.
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