Statistical models based ECG classification

This chapter gives a comprehensible description of two statistical approaches successfully employed to the problem of beat modeling and classification: hidden Markov models and hidden Markov treesMarkov trees. The HMM is a stochastic state machine which models a beat sequence as a cyclostationary Markovian process. It offers the advantage of performing both beat modeling and classification through a unique statistical approach. The HMT exploits the persistence property of the wavelet transform by associating to each wavelet coefficient a state and the states are connected across scales to form a probabilistic graph. This method can also be used for signal segmentation.