Deploying Deep Learning Models For the Classification of Arrhythmias

Arrhythmia is a cause of irregular heartbeat. It means the heart is not beating in a regular rhythm. We identify this arrhythmia through Electrocardiogram(ECG) signals. ECG features like original variation, relative position, and variation trends are used to classify arrhythmia. We have used CNN, LSTM, and hybrid CNN-LSTM models are implemented for addressing this problem and to check which model is better for classifying the arrhythmia based on ACC, SEN, and SPE score.