Electrocardiogram (ECG) signal classification method and device

Abstract

The invention relates to the technical field of ECG analysis and in particular relates to an ECG signal classification method and device. The ECG signal classification method comprises the following steps: a, segmenting the ECG signal, and respectively acquiring training set data and test set data; b, performing model training on the training set data through deep learning, and constructing a prediction classification model; and c, performing ECG signal classification on the test set data through the prediction classification model. According to the embodiment of the invention, the training set is subjected to model training through deep learning so as to obtain the prediction classification model, and the ECG signal classification is performed through the prediction classification model, so that incompleteness caused by artificial design characteristics is reduced, the ECG signal classification accuracy is improved, and more types of heart rate variability can be classified.

Description

technical field [0001] The invention relates to the technical field of electrocardiographic analysis, in particular to a method and device for classifying electrocardiographic signals. Background technique [0002] Arrhythmia is a common phenomenon in the crowd. Serious arrhythmia will immediately threaten human life. Therefore, timely detection of arrhythmia is of great significance to prevent heart disease and sudden cardiac death. In the ECG information, the P wave (the waveform generated when the left and right atria are depolarized during the electrocardiogram), the QPS wave (the wave group with the largest amplitude in the normal ECG), and the T wave (the wave that appeared after the last wave group paused), representing the ventricles The repolarization of the heart to prepare for the next ventricular depolarization) is an important characteristic wave of the ECG signal, and their characteristic change information is an important basis for the analysis and diagnosis o...

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Problems solved by technology

[0013] The present invention provides a method and device for classifying electrocardiographic signals, aiming to solve the problem of limited classification types of existing electrocardiographic signal arrhythmia classification methods, confusion in the definition of arrhythmia types, and no classification of electrocardiographic signals through deep learning. technical problem

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