Valentina De Vitis
A Deep Learning Method for Automatic Detection of Most Relevant ECG Features.
Rel. Eros Gian Alessandro Pasero, Vincenzo Randazzo. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022
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Abstract
The main cause of mortality in the world are cardiovascular diseases (CVDs). Each year, around 17.9 million people die from CVDs and this number represents the 32% of all global deaths. Early diagnosis and treatment are very important for people which present high cardiovascular risk. Irregularities in the heartbeat rhythm are defined "Arrhythmias" and they can rarely occur during human's life. This kind of problems can lead to some complications that may constitute an immediate risk for life and may cause potentially fatal events. The premature classification and detection of arrhythmias is a good starting point for cardiac disease diagnosis. The most important element to detect these events is the electrocardiogram (ECG), a non-expensive, non-invasive method, which gives a record of heart's electrical functionality.
The interpretation process of ECG requires a high degree of training and is time-consuming
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