An approach for ECG classification using wavelets and Markov Model

In this paper we purpose a method for the classification of the signal ECG, this method is based on the use of the ergodic Markov model the data used was obtained from the MIT-BIH arrhythmia data base for two categories. each beat is isolated and its discrete wavelet transform is calculated and the Vectorial Quantization is applied the parameters of the Markov model are computed for different number of states. The results presented are discussed.