Automated Diagnosis of Heart Arrhythmia Using Recurrent Neural Network

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K. Jummelal
M.Sai Prathyusha
U. Monika Sai
A. Sravanthi


The term "cardiac arrhythmia" refers to irregular heartbeats. This study's major goal is to use deep learning algorithms to detect cardiac arrhythmias from ECG signals with the least amount of data pre-processing necessary. To automatically detect irregularities, our method combines recurrent structures with CNN, such as recurrent neural networks (RNN), long short-term memories (LSTM), gated recurrent units (GRU), and a mixture of CNN and recurrent structures. Contrary to traditional analysis approaches, deep learning algorithms do not rely on feature extraction-based analysis techniques. All tests are executed for 1000 epochs within a defined range of learning rates to ascertain the best parameters for the deep learning approaches.

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How to Cite
K. Jummelal, M.Sai Prathyusha, U. Monika Sai, & A. Sravanthi. (2023). Automated Diagnosis of Heart Arrhythmia Using Recurrent Neural Network. Journal of Coastal Life Medicine, 11(2), 681–685. Retrieved from


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