Hidden Markov Models for Classification of Heart Rate Variability in RR Time Series
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Discrete hidden Markov models (HMM) are trained in order to differentiate between RR series of persons in normal sinus rhythm and of post-myocardial infarct patients with six or more ventricular premature complexes per hour during 24 hour Holter ECG recording.