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Classification of Heartbeats using Morphological and Dynamic Features of ECG Signal


Bhagyashri Raghunath Birajdar , WIT,Solapur; Mrutunjay R. Madki, WIT,Solapur


ECG signal, heartbeat classification, independent component analysis, RR features


This paper focuses a new approach for heartbeat classification based on a combination of morphological and dynamic features of ECG signal. In this study, wavelet transform and independent component analysis (ICA) will be applied separately to each ECG signal to extract morphological features. In addition, RR interval information will be computed to provide dynamic features. These two different types of features will be concatenated and a classifier will be utilized for the classification of heartbeats into one of five classes. The work will be validated on the baseline MIT/BIH arrhythmia database. The purpose of the paper is to achieve higher accuracy over other state-of-the-art methods for heartbeat classification.

Other Details

Paper ID: IJSRDV3I60259
Published in: Volume : 3, Issue : 6
Publication Date: 01/09/2015
Page(s): 691-693

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