Atrial fibrillation recognition method, device and equipment, and computer-readable storage medium

Abstract

The invention provides atrial fibrillation identification method, device and equipment and a computer-readable storage medium. The method includes the steps: the R wave crest position in an electrocardiogram signal to be identified is obtained, and then heart rate variability characteristics and heart rate segments are determined according to the R wave crest position; the cardiac characteristicsof each cardiac segment are acquired to form a cardiac characteristic group; and finally, the heart rate variability and heart rate characteristics are input into the model of atrial fibrillation recognition, and the results of atrial fibrillation recognition are obtained. The invention can effectively identify atrial fibrillation by inputting heart rate variability characteristics and heart ratecharacteristics of an electrocardiogram signal into a pre-trained atrial fibrillation identification model, thereby realizing the improvement of reliability and accuracy of atrial fibrillation identification.

Description

technical field [0001] The present invention relates to the technical field of electrocardiogram monitoring, in particular to a method, device, equipment and computer-readable storage medium for identifying atrial fibrillation. Background technique [0002] Atrial fibrillation (AF for short) is the most common sustained chronic cardiac arrhythmia, often arising from disordered atrial activity and irregular atrial compression. The incidence of atrial fibrillation increases with age. Atrial fibrillation is closely related to various diseases such as stroke, heart failure, coronary heart disease, and thrombosis. Early identification of atrial fibrillation can help patients discover cardiac abnormalities in time and reduce the morbidity and mortality caused by heart diseases. [0003] In the prior art, it is possible to identify whether atrial fibrillation has occurred by analyzing electrocardiographic signals, but the current identification method for atrial fibrillation based...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, the occurrence of atrial fibrillation can be identified by analyzing the ECG signal, but the current identification method based on heart rate variability is difficult to meet the clinical diagnosis standard in terms of reliability and accuracy

In recent years, some atrial fibrillation identification methods based on traditional machine learning have emerged. However, due to the complexity of atrial fibrillation signals, only a few manually extracted features combined with traditional machine learning methods are not enough to accurately identify atrial fibrillation.

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