An Efficient Heartbeats Classifier Based on Convolutional Neural Network


Authors : SHAIK CHANDINI; DONELLI BABY SRILAKSHMI; KONDAMURU SRI AKHILA

Volume/Issue : Volume 7 - 2022, Issue 5 - May

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3xZmBnE

DOI : https://doi.org/10.5281/zenodo.6662978

Recently, deep learning models have arrived as assuring methods for the diagnosis of various diseases. Cardiac disease is one of the leading life-threatening diseases on global scale. The aim of this paper is to propose a heartbeat classifier from the electrocardiogram by using CNN. The proposed Electrocardiogram classification model is designed with a CNN configuration to classify heartbeat arrhythmias in less time. Already existing designs like machine learning techniques are time-consuming and needs extensive experimentation. To overcome this problems, we are using CNN model for ECG Classification.

Keywords : ECG analysis, cardiac arrhythmias, ECG classification, deep learning and convolutional neural networks.

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