Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/4023
Title: Classification of electrocardiogram signals
Authors: Botros, Jad
Advisors: Abche, Antoine 
Subjects: Electrocardiography
Signal processing--Digital techniques
Issue Date: 2019
Abstract: 
The electrocardiogram (referred to as ECG) has and plays an imperative role in analyzing and monitoring the patients. It is also very important in diagnosing different cardiac diseases from which we can cite cardiac arrhythmias. Cardiac arrhythmias can be very severe and can threaten the patients life. When diagnosing a cardiac arrhythmia, the patient is asked to wear a Holter monitor or an event recorder, two types of portable devices which their leads are attached to the patient in order to record and monitor the hearts electrical activity over a certain period (long). Due to the large amount of data generated by such devices, a computer aided diagnosis tool is needed to help detecting and classifying the signals. The objective of this work is a small step to detect the cardiac arrhythmias and to classify the collected ECG signals based on their ECG signals temporal features. The approach is able to differentiate between the tested arrhythmia classes with an acceptable accuracy.
Description: 
Includes bibliographical references (p. 83-86).

Supervised by Dr. Antoine Abche.
URI: https://scholarhub.balamand.edu.lb/handle/uob/4023
Rights: This object is protected by copyright, and is made available here for research and educational purposes. Permission to reuse, publish, or reproduce the object beyond the personal and educational use exceptions must be obtained from the copyright holder
Ezproxy URL: Link to full text
Type: Thesis
Appears in Collections:UOB Theses and Projects

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