Atrial fibrillation detecting method and system

Abstract

The invention relates to an atrial fibrillation detection method and system. A condition that whether signals have P wave or not is added while the characteristic reflecting RR interval irregularity of the ECG signals is extracted, so that the problem of false detection of sinus arrhythmia signals is solved; a BP neural network method is adopted to replace simple logic conditions to judge atrial fibrillation signals, so that atrial fibrillation detecting accuracy when input RR interval number is small is improved.

Description

technical field [0001] The invention relates to a method for detecting atrial fibrillation, and at the same time, the invention also relates to a detection system for atrial fibrillation. Background technique [0002] Atrial fibrillation is one of the most common arrhythmias, with an incidence rate of 0.3% to 0.4% in adults. With the increase of age, the incidence rate doubles, and the incidence rate of those over 75 years old is close to 10%. Electrical activation of the normal heart begins at the sinoatrial node. Since the sinoatrial node is located at the junction of the right atrium and the superior vena cava, the excitation of the sinoatrial node is first transmitted to the right atrium, and then transmitted to the left atrium through the interatrial bundle, forming a P wave on the electrocardiogram. The excitation is conducted to the atrioventricular node along the antero-middle-posterior nodal bundle. Due to the slow conduction velocity of the atrioventricular node,...

AI Technical Summary

Problems solved by technology

However, this method will have the problem of false detection for sinus arrhythmia signal (because its RR interval also has the characteristics of absolute irregularity of RR interval).

And simply use logical conditions to determine atrial fibrillation, when the number of RR intervals is small, there will be a problem of low accuracy

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