Cardiovascular diseases are a set of disorders of the heart and blood vessels, including
coronary artery disease, cardiovascular disease, cardiac arrests, and other conditions.
According to the World Health Organization, four out of five deaths from
cardiovascular diseases occur prematurely in people under 70 years of age. The
diagnosis of these diseases is usually made through an electrocardiogram (ECG), which
records the heart’s electrical activity. The standard ECGs has 12 leads, each
representing graphically the differences in potential in different parts of the body,
allowing for the analysis of the cardiac cycle and the identification of anomalies. The
most important waveforms in the ECG are, P, Q, R, S and T, with the set of them being
called the QRS complex, representing ventricular depolarization. Five characteristic
anomalies of the QRS complex denote cardiac pathologies. This research was based on
the detection of the QRS complex in 12-lead ECGs using convolutional neural
networks, improving on previous work by considering the presence of these anomalies.
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