Journal of Machine and Computing

Monitoring and Recognition of Heart Health using Heartbeat Classification with Deep Learning and IoT

Journal of Machine and Computing

Received On : 15 January 2023

Revised On : 22 April 2023

Accepted On : 30 May 2023

Published On : 05 July 2023

Volume 03, Issue 03

Pages : 326-339


The advancement and innovations in the field of science and technology paved way for various advanced treatments in the field of medicine. They are implemented using sensors, and computer-aided designs with artificial intelligence techniques. This helps in the detection of serious health constraints at an earlier stage with appropriate treatments using decision-making techniques. One of the important health concerns that are increasing rapidly is cardiovascular disorders. This includes Arrhythmia and Myocardial Infarction. Earlier prediction and classification can protect them from serious constraints. They are diagnosed using the Electrocardiogram (ECG). To obtain accurate results, artificial intelligence techniques are implemented to extract the optimum output. The proposed system includes the detection and classification using deep learning techniques with the Internet of Things (IoT). The existing heartbeat detection system is overcome using a deep convolutional neural network. This helps in the implementation of automatic heartbeat detection and identification of abnormalities. The ECG signals are pre-processed with segmentation and feature extraction techniques. The classification and identification of constraints in the functioning of the heart are identified using optimization algorithms. The proposed system is trained, tested, and evaluated using the MIT-BIH arrhythmia database. The accuracy and efficiency of the proposed system are 99.98% using the MIT-BIH dataset.


Cardiovascular System, Arrhythmia, Myocardial Infarction, Artificial Intelligence, Decision Making Techniques, Electrocardiogram, Deep Learning, Optimization Algorithm.

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We would like to thank Reviewers for taking the time and effort necessary to review the manuscript. We sincerely appreciate all valuable comments and suggestions, which helped us to improve the quality of the manuscript.


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Cite this article

Arulkumar V, Vinod D, Devipriya A, Chemmalar Selvi G, Surendran S and Mohammad Arif, “Monitoring and Recognition of Heart Health using Heartbeat Classification with Deep Learning and IoT, Journal of Machine and Computing, vol.3, no.3, pp. 326-339, July 2023. doi: 10.53759/7669/jmc202303028.


© 2023 Arulkumar V, Vinod D, Devipriya A, Chemmalar Selvi G, Surendran S and Mohammad Arif. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.