Classifying electrocardiograph waveforms using trained deep learning neural network based on wavelet representation
Noor Yahya Jawad,
Ahmed Mohammed Merza,
Hussein Tami Sim
Abstract:<span lang="EN-US">Due to the rise in cardiac patients, an automated system that can identify different heart disorders has been created to lighten and distribute the duty of physicians. This research uses three different electrocardiograph (ECG) signals as indicators of a person's cardiac problems: Normal sinus rhythm (NSR), arrhythmia (ARR), and congestive heart failure (CHF). The continuous wavelet transform (CWT) provides the mechanism for classifying the 190 individual cases of ECG data into a 2-dim… Show more
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