A Survey on Automated Detection of Cardiac Arrhythmia

Authors

  • Aniket Patil  Department of Computer Engineering, Zeal College of Engineering and Research, Pune, Maharashtra, India
  • Sachin Patil  Department of Computer Engineering, Zeal College of Engineering and Research, Pune, Maharashtra, India

Keywords:

Arrhythmia detection, Artificial Intelligence (AI), Electrocardiogram (ECG), Classification.

Abstract

Cardiac arrhythmia is a potentially life-threatening condition which is generally detected by a doctor with the help of an electrocardiogram (ECG). An arrhythmia is an irregular heartbeat which is caused when the electrical signals controlling the heart are at fault. In the modern world of Artificial Intelligence (AI) and Machine Learning (ML) we can automate the process of detection of such diseases to avoid manual delays in diagnosis in a world affected by COVID-19, where the medical personnel are already overburdened. Automating arrhythmia detection is a problem of classification of heartbeats into normal or the different classes of arrhythmias. It not only reduces the time for diagnosis but also reduces the possibilities of manual errors preventing accurate diagnosis. In this survey we systematically explore the various methodologies and algorithms which have been proposed prior with respect to their advantages, prediction metrics, datasets and gaps. The gap analysis sheds light on the disadvantages of the explored methods and hence provides the future scope of research for them.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2022-04-30

Issue

Volume 9, Issue 2, March-April-2022

Section

Research Articles

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How to Cite

[1]
Aniket Patil, Sachin Patil, " A Survey on Automated Detection of Cardiac Arrhythmia, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 9, Issue 2, pp.449-458, March-April-2022.