Arrhythmia Classification Method Based on SECNN-LSTM
Xiujuan Sun,
Guohui Wei,
Shan Zhang
et al.
Abstract:In order to improve the recognition and prediction accuracy of automatic classification of ECG signals, this paper proposes an arrhythmia classification method based on SECNN-LSTM. First, ECG signal is preprocessed, and the data is resampled for the problem of data imbalance, then the SECNN-LSTM network model is built. The spatial features of the signal are extracted by SECNN model and the front and back dependencies of the feature information are captured by LSTM model. The method has been tested and verified… Show more
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