Periodic monitoring method and device based on premature beat signal in wearable electrocardiosignal

Abstract

The invention discloses a periodic monitoring method and a device based on premature beat signals in a wearable electrocardiosignal, which consist of a wearable electrocardiosignal detection module and a long-time premature beat heart beat detection module. A reading unit in the long-time premature beat heart beat detection module reads the heart beat to be detected, after the heart beat type is determined by a real-time premature beat detection unit, a primary template generation unit and a secondary template generation unit respectively generate a primary template and a secondary template, and finally the heart beat type is determined through a primary-secondary heart beat detection unit, and on the basis of a normal heart beat, whether the heart beat type is an supraventricular premature beat heart beat or a normal heart beat is judged through an supraventricular premature beat detection unit, so that the long-time comfortable monitoring of ventricular premature beat and supraventricular premature beat under daily activities is achieved. The periodic monitoring method and the device based on premature beat signals in the wearable electrocardiosignal have the advantages of simplealgorithm, convenient operation, and applicability to the requirements of different users.

Description

[0001] Field of study [0002] The invention relates to the technical field of signal detection and medical equipment electronics, in particular to a method and device for periodic monitoring of premature beat signals in wearable electrocardiogram signals. Background technique [0003] Premature contractions, also known as premature contractions or premature beats, are one of the most common multiple cardiac arrhythmias. According to the different mechanisms, it can be divided into two types: ventricular premature beats and supraventricular premature beats, of which the most common and common is ventricular premature beats, followed by supraventricular premature beats. Premature beats can occur in normal people or in patients with structural heart disease, commonly seen in myocarditis, rheumatic heart disease, etc. Correct detection of premature beat signals is the key to improving the accuracy of arrhythmia event detection It has important practical value for improving the d...

AI Technical Summary

Problems solved by technology

In this case, the process of feature extraction is relatively complicated, and the automatic ECG analysis is obviously affected by the result of feature extraction. Generally, more feature sets are needed to achieve better classification results. It will increase the computing complexity of the terminal, the mobile platform is difficult to load, and the monitoring effect cannot be realized effectively; The data information contained in the data segment is small, especially the dynamic ECG signal collected in the wearable environment, the baseline drift is large, and the motion noise is large. Premature beat detection in the short-term data segment is easy to cause false detection and missed detection. Therefore, it is necessary to Develop a periodic, long-term wearable detection device and algorithm to achieve comfortable, simple and fast premature beat monitoring

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