IMPLEMENTATION OF AN ARTIFICIAL INTELLIGENCE-BASED ECG ACQUISITION SYSTEM FOR THE DETECTION OF CARDIAC ABNORMALITIES
Achraf Benba
achraf.benba@um5s.net.maMohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies (Morocco)
https://orcid.org/0000-0001-7939-0790
Fatima Zahra El Attaoui
Mohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies (Morocco)
http://orcid.org/0009-0001-0196-0500
Sara Sandabad
Ecole Normale Supérieure de l'Enseignement Technique de Mohammadia, Electrical Engineering and Intelligent Systems, Hassan II University of Casablanca (Morocco)
http://orcid.org/0000-0002-0813-6178
Abstract
The electrocardiogram (ECG) is a common test that measures the electrical activity of the heart. On the ECG, several cardiac abnormalities can be seen, including arrhythmias, which are one of the major causes of cardiac mortality worldwide. The objective for the research community is accurate and automated cardiovascular analysis, especially given the maturity of artificial intelligence technology and its contribution to the health area. The goal of this effort is to create an acquisition system and use artificial intelligence to classify ECG readings. This system is designed in two parts: the first is the signal acquisition using the ECG Module AD8232; the obtained signal is a single derivation that has been amplified and filtered. The second section is the classification for heart illness identification; the suggested model is a deep convolutional neural network with 12 layers that was able to categorize five types of heartbeats from the MIT-BIH arrhythmia database. The results were encouraging, and the embedded system was built.
Keywords:
electrocardiogram, arrhythmias, artificial intelligence, convolution neural networkReferences
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Authors
Achraf Benbaachraf.benba@um5s.net.ma
Mohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies Morocco
https://orcid.org/0000-0001-7939-0790
Authors
Fatima Zahra El AttaouiMohammed V University in Rabat, Ecole Nationale Supérieure d'Arts et Métiers, Electronic Systems Sensors and Nanobiotechnologies Morocco
http://orcid.org/0009-0001-0196-0500
Authors
Sara SandabadEcole Normale Supérieure de l'Enseignement Technique de Mohammadia, Electrical Engineering and Intelligent Systems, Hassan II University of Casablanca Morocco
http://orcid.org/0000-0002-0813-6178
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