CLASSIFICATION OF ECG ARRHYTHMIAS USING DISCRETE WAVELET TRANSFORM AND NEURAL NETWORKS

@article{Sarkaleh2012CLASSIFICATIONOE,
  title={CLASSIFICATION OF ECG ARRHYTHMIAS USING DISCRETE WAVELET TRANSFORM AND NEURAL NETWORKS},
  author={Maedeh Kiani Sarkaleh and Asadollah Shahbahrami},
  journal={International Journal of Computer Science, Engineering and Applications},
  year={2012},
  volume={2},
  pages={1-13}
}
  • M. Sarkaleh, A. Shahbahrami
  • Published 29 February 2012
  • Computer Science
  • International Journal of Computer Science, Engineering and Applications
Automatic recognition of cardiac arrhythmias is important for diagnosis of cardiac abnormalies. Several algorithms have been proposed to classify ECG arrhythmias; however, they cannot perform very well. Therefore, in this paper, an expert system for ElectroCardioGram (ECG) arrhythmia classification is proposed. Discrete wavelet transform is used for processing ECG recordings, and extracting some features, and the Multi-Layer Perceptron (MLP) neural network performs the classification task. Two… 
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