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Predicting Cardiac Arrhythmia Using QRS Detection and Multilayer Perceptron

  • Harika Gundala
  • Mayank Sethia
  • Mehul Sethia
  • Shreyas Gonjari
  • Akshay Gugale
  • Rajeshkannan RegunathanEmail author
Conference paper
  • 32 Downloads
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 169)

Abstract

Most deaths occur around the world because of cardiac disorders. Cardiac rhythm disorders may cause severe strokes and heart diseases. Arrhythmias occur when the electric signals to the heart are irregular or not working properly. Mostly, these irregular heartbeats feel like racing hearts. Many times, arrhythmias are harmless, but if they are abnormal or they result due to damaged heart, then they can be fatal. Cardiac arrhythmia, being the leading cause of death in both men and women, can be prevented with the early and correct diagnosis. In this paper, the focus is mainly on predicting whether the patient has cardiac arrhythmia or not based on electrocardiography (ECG) reports. Pan–Tompkins algorithm has been used for QRS detection which predicts the abnormal deflections that lead to the arrhythmic events. The same reports have been used to classify which type of cardiac arrhythmia the patient has using Multilayer Perceptron (MLP) algorithm.

Keywords

Cardiac arrhythmia QRS detection ECG signals Pan–Tompkins algorithm Multilayer perceptron 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Harika Gundala
    • 1
  • Mayank Sethia
    • 1
  • Mehul Sethia
    • 1
  • Shreyas Gonjari
    • 1
  • Akshay Gugale
    • 1
  • Rajeshkannan Regunathan
    • 1
    Email author
  1. 1.School of Computer Science EngineeringVellore Institute of TechnologyVelloreIndia

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