ABSTRACT This article focuses on the features extraction from time series and signals using Fourier and Wavelet transforms. This task will be carried out on an electrocardiogram (ECG) dataset in order to classify three groups of people: those with cardiac arrhythmia (ARR), congestive heart failure (CHF) and normal sinus rhythm (NSR). Our approach consists of using scaleogram (i.e. 2D representation of 1D extracted features) as an input to train a Neural Network (NN). We conducted the different tasks using python as a programming language. The…
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