Abstract Arrhythmias can be detected using an ECG signal, which is an important tool in the healthcare industry. ECG overall variation trends, original variation features, and their relative positions are used to classify arrhythmias according to sphere knowledge and large-scale data analysis. They haven’t been fully explored by being styles. CNN and hybrid CNN-LSTM models are used to address this problem. A LSTM and CNN are used to separate the ECG’s overall variation trends and its unique features. In this proje…