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Predicting Cardiac Arrhythmia Using QRS Detection and Multilayer Perceptron
H. Gundala, M. Sethia, M. Sethia, S. Gonjari, A. Gugale,
Published in Springer
2020
Volume: 169
   
Pages: 781 - 789
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. © 2020, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetSmart Innovation, Systems and Technologies
PublisherData powered by TypesetSpringer
ISSN21903018