Data is a 162-by-65536 matrix where each row is an ECG recording sampled at 128 hertz. Load(fullfile(tempdir, 'ECGData', 'ECGData.mat'))ĮCGData is a structure array with two fields: Data and Labels. The file physionet_ECG_data-main.zip contains Modify the subsequent instructions for unzipping and loading the data if you choose to download the data in a folder different from tempdir. The instructions for this example assume you have downloaded the file to your temporary directory, ( tempdir in MATLAB). Save the file physionet_ECG_data-main.zip in a folder where you have write permission. To download the data, click Code and select Download ZIP. The first step is to download the data from the GitHub repository. The goal is to train a classifier to distinguish between arrhythmia (ARR), congestive heart failure (CHF), and normal sinus rhythm (NSR). In total, there are 96 recordings from persons with arrhythmia, 30 recordings from persons with congestive heart failure, and 36 recordings from persons with normal sinus rhythms. The example uses 162 ECG recordings from three PhysioNet databases: MIT-BIH Arrhythmia Database, MIT-BIH Normal Sinus Rhythm Database, and The BIDMC Congestive Heart Failure Database. This example uses ECG data obtained from three groups, or classes, of people: persons with cardiac arrhythmia, persons with congestive heart failure, and persons with normal sinus rhythms.
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