  This paper present an electrocardiogram (ECG) beat classification method
based on waveform similarity and RR interval. The purpose of the method is to
classify six types of heart beats (normal beat, atrial premature beat, paced
beat, premature ventricular beat, left bundle branch block beat and right
bundle branch block beat). The electrocardiogram signal is first denoised using
wavelet transform based techniques. Heart beats of 128 samples data centered on
the R peak are extracted from the ECG signal and thence reduced to 16 samples
data to constitute a feature. RR intervals surrounding the beat are also
exploited as feature. A database of annotated beats is built for the classifier
for waveform comparison to unknown beats. Tested on 46 records in the MIT/BIH
arrhythmia database, the method shows classification rate of 97.52%.
