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CARDIAC ARRHYTHMIA DETECTOR USING CNN APPLICATION

    Authors

    • Dr. R. Kishore Kanna 1
    • U. Mutheeswaran 1
    • V. Subha Ramya 1
    • Dr. R. Vasuki 2
    • Dr. R Gomalavalli 3

    1 Assistant Professor, Department of Biomedical Engineering, Vels Institute of Science, Technology and Advanced Studies [VISTAS]

    2 Professor, Department of Biomedical Engineering, Bharath Institute of Higher Education and Research

    3 Professor, Department of Electronics and Communication Engineering, Siddharth Institute of Engineering and Technology

,

Document Type : Research Article

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Abstract

In medical practise, an electrocardiogram (ECG) is a crucial indicator tool for assessing cardiovascular arrhythmias. In this study, a machine learning system is used to compare patient ECGs and perform programmed ECG arrhythmia identification. The system was previously tuned based on an overall image informational index. Arrhythmias are more prevalent in those over the age of 60. A convolutional neural network (particularly, Alex Net) is utilised to extract features, and the highlights are then passed via a basic back spread neural network to finish the classification. The fundamental purpose of this research is to provide a simple, effective, and relevant learning strategy for categorising the three types of heart conditions (cardiac defects) so that a diagnosis may be made. The findings showed that when a moving deep learning highlight extractor was combined with a standard back proliferation neural architecture, very elite rates could be achieved. In a comparative analysis, validation accuracy was shown to be 100 percent in Google Net, 94 percent in Squeeze Net, and about 97.33 percent in Alex Net.

Keywords

  • ECG
  • Cardiac
  • pattern recognition
  • CWT
  • CNN
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    • Article View: 91
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European Journal of Molecular & Clinical Medicine
Volume 9, Issue 9 - Issue Serial Number 9
December 2022
Page 31-38
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  • Article View: 91
  • PDF Download: 96

APA

Kanna, D. R. K., Mutheeswaran, U., Ramya, V. S., Vasuki, D. R., & Gomalavalli, D. R. (2023). CARDIAC ARRHYTHMIA DETECTOR USING CNN APPLICATION. European Journal of Molecular & Clinical Medicine, 9(9), 31-38.

MLA

Dr. R. Kishore Kanna; U. Mutheeswaran; V. Subha Ramya; Dr. R. Vasuki; Dr. R Gomalavalli. "CARDIAC ARRHYTHMIA DETECTOR USING CNN APPLICATION". European Journal of Molecular & Clinical Medicine, 9, 9, 2023, 31-38.

HARVARD

Kanna, D. R. K., Mutheeswaran, U., Ramya, V. S., Vasuki, D. R., Gomalavalli, D. R. (2023). 'CARDIAC ARRHYTHMIA DETECTOR USING CNN APPLICATION', European Journal of Molecular & Clinical Medicine, 9(9), pp. 31-38.

VANCOUVER

Kanna, D. R. K., Mutheeswaran, U., Ramya, V. S., Vasuki, D. R., Gomalavalli, D. R. CARDIAC ARRHYTHMIA DETECTOR USING CNN APPLICATION. European Journal of Molecular & Clinical Medicine, 2023; 9(9): 31-38.

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