An Automatic Classification Method of ECG Signal Based on Single Lead

Abstract

The present invention provides a method for automatic classification of electrocardiographic signals based on a single lead, which receives limb lead electrocardiographic signals through Web socket; uses wavelet median threshold method to remove noise; then uses Pan-Tompkins method for R-wave detection, Cutting the signal based on the R wave and calculating the RR interval characteristics, the obtained ECG segments are sequentially subjected to empirical mode decomposition, Gaussian random projection matrix, polynomial fitting, and interval extreme value operation to obtain the corresponding eigenvectors; The vector is standardized so that it conforms to the standard normal distribution, and the standardized feature vector is input into the trained XGboost model, and the corresponding detection value is output. The present invention overcomes the problem of individual ECG specificity. At the same time, the method runs on the server side, reducing the pressure on the client side. This method has a high reference value for the detection results of N and V abnormal heart rhythms.

Description

technical field [0001] The invention belongs to the field of health detection and relates to a method for automatically classifying electrocardiographic signals based on a single lead. Background technique [0002] Cardiovascular disease is a common chronic disease characterized by acute onset and high mortality, which seriously threatens people's life and health. With the progress of society, people's quality of life is gradually improving, and the morbidity and mortality of cardiovascular diseases in our country are also increasing, and tend to be younger and civilian. According to the "China Cardiovascular Disease Report 2017", cardiovascular disease ranks first in the total death causes of urban and rural residents, and the incidence rate continues to rise. Against the backdrop of an increasingly aging population, accelerated urbanization, and the prevalence of sub-healthy lifestyles among residents, the expansion trend of cardiovascular diseases is obvious, leading to ...

AI Technical Summary

Problems solved by technology

[0004] The task of the present invention is to develop on the basis of the original technology, to provide an automatic ECG classification method, suitable for application in remote ECG monitoring systems, to solve the problem of low efficiency during dynamic ECG feature extraction, and to adopt high-performance classification device, enhance the effect of real-time monitoring, and improve the accuracy of ECG classification

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