ECG classification as a dynamic process based on a spiking neural network

2024

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DOI 10.31649/1681-7893-2024-48-2-68-77
Data confidence 70 medium
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Abstract

The article analyzes the ECG classifying methods. A method of dynamic ECG classification using spiking neural networks is proposed. Dynamic parameters are selected, which are a representation of the ECG signal in a time series. These parameters are fed into the input of a spiking neural network, which outputs both a single heartbeat and a full ECG study. The developed spiking neural network has fast learning and uses large amounts of data for training.