Abstract
According to the World Health Organization (WHO), cardiovascular disease (CVD) is the leading cause of death and disability worldwide, killing more than 17 million people every year. This toll accounts for a third of all deaths worldwide and half of all noncommunicable disease-related deaths. More than 80% of these deaths occur in low- and middle-income countries. Arrhythmia, also known as cardiac arrhythmia or heart arrhythmia, is a CVD disease that refers to any irregular change in the normal rhythms of the heart. The electrocardiogram (ECG) signal is a test that records the strength and timing of electrical events of the cardiac cycle in the heart. This chapter helps understand how to classify ECG signals as normal and different types of arrhythmia through convolutional neural networks (CNNs).
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