A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Classification Of Ecg Arrhythmias Using Discrete Wavelet Transform and Neural Networks
2012
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
doi:10.5121/ijcsea.2012.2101
fatcat:qojtjuqdy5ed7kglfnj5yjwuhq