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Proposed classification method

Proposed classification method

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Fig. 1. Basic structure of an RNN [19].
Fig. 2. Proposed classification method
Fig. 3. Signals from the selected database.
Fig. 4. Representation of a spectrogram of a normal signal and with FA.
+2 Fig. 5. Bidirectional LSTM hybrid neural network.
Implementation of Time-Frequency Moments for the Classification of Atrial Fibrillation Sequences Through a Bidirectional Long-Short Term Memory Network
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  • Sep 2022
This article proposes a method to classify atrial fibrillation signals using time-frequency characteristics through a BiLSTM network. The experiment was performed with the ECG signals, which are part of the PhysioNet CinC 2017 database. In addition to the BiLSTM network, machine learning algorithms such as k Nearest Neighbors, Linear SVM, RBF SVM,...
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