Ruairí O'Reilly

Ruairí O'Reilly

Lecturer in Computer Science at Munster Technological University. Research in Explainable AI, generative AI evaluation, biomedical AI, fairness and decision support.

Arrhythmia Detection in ECG Signals Using a Multilayer Perceptron Network

Published in The 27th Irish Conference on Artificial Intelligence and Cognitive Science, 2019

Abstract

Electrocardiography (ECG) is a form of physiological data used to record the electrical activity of the heart. Numerous researchers have proposed and developed methods to extract features from the ECG signal (for example, R-R segment, P-R segment). These features can be used to analyse and classify various forms of heart arrhythmia. In this work, a method for ECG classification that employs a generalised signal pre-processing technique and uses a Multi-Layer Perceptron network to classify arrhythmia per the AAMI EC57 standard accurately is presented. The method is trained and evaluated using PhysioNet’s MIT-BIH dataset, and an average accuracy of 98.72% is achieved. The proposed methodology is comparable to state-of-the-art CNN models, both in terms of accuracy and efficiency.

Paper ResearchGate

Recommended citation: Gaurav Kumar, Urja Pawar and Ruairi O'Reilly (2019). “Arrhythmia Detection in ECG Signals Using a Multilayer Perceptron Network.” The 27th Irish Conference on Artificial Intelligence and Cognitive Science.
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