2019 IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health (BECITHCON) 2019

DOI: 10.1109/becithcon48839.2019.9063183

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ECG Heartbeat Classification: A Comparative Performance Analysis between One and Two Dimensional Convolutional Neural Network

Alif Bin Abdul Qayyum

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Tanveerul Islam

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Cited by 4 publications

References 14 publications

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Detecting Heart Arrhythmias Using Deep Learning Algorithms

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et al. 2023

Convergence of Cloud With AI for Big Data Analytics

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No abstract

Detecting Heart Arrhythmias Using Deep Learning Algorithms

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et al. 2023

Convergence of Cloud With AI for Big Data Analytics

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ElectrApp: Deep learning framework to enhance cardiac arrhythmia detection

L Echeverry,

Lopez Flórez,

Guapacha

et al. 2024

Logic Journal of the IGPL

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Medical specialists who diagnose patients with cardiovascular arrhythmias are not promptly available in rural areas. The proposed information system provides access to upload the data to a cloud-based processing module in which different arrhythmias are classified, allowing the classification of various arrhythmias to solve the scarcity of physicians in remote areas through an automatic system that helps with the diagnosis. This information system has a controller module for the operation that manages data collection, processing, beautification and visualization tasks. We used the MIT-BIH Arrhythmia Database during the training and validation of the classification module. The module uses deep learning to identify five different types of heartbeats according to standards, reporting 98.9% accuracy. The information system will improve health coverage in the prediagnosis of cardiovascular diseases.

Using Neural Networks for ECG Classification

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2022

2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics (SAMI)

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