The invention discloses an arrhythmia classification system and method using a deep neural network. An arrhythmia classification method using a deep neural network according to one aspect of the present invention comprises the steps of: receiving an ECG signal; preprocessing the received ECG signal to enable the ECG signal to be suitable for a deep neural network algorithm; detecting a peak valueof a P-QRS-T wave in the preprocessed ECG signal; a step of constructing a data set by integrating the detected peak value of the P-QRS-T wave with tag data to construct a single file; and a step of classifying the arrhythmias by applying a deep neural network including an input layer, a hidden layer, and an output layer to a peak value and a data set of the P-QRS-T wave.
ARRHYTHMIA CLASSIFICATION SYSTEM AND METHOD USING DEEP NEURAL NETWORK