Hidden Markov Models for Classification of Heart Rate Variability in RR Time Series

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.