Automatic electrocardiosignal classification method based on single channel

Abstract

The invention provides an automatic electrocardiosignal classification method based on single channel. The method comprises the steps that a limb channel electrocardiosignal is received through Web socket; a wavelet median threshold method is adopted to perform electrocardiosignal denoising; a Pan-Tompkins method is used for conducting R wave detection, the electrocardiosignal is segmented based on R wave to resolve RR period characteristics, corresponding characteristics vectors are obtained by sequentially conducting empirical mode decomposition, Gaussian random projection matrix, polynomialfitting and interval extremum on obtained electrocardiogram segments; normalization is conducted on obtained characteristic features to allow the characteristic features to be conformed to standardized normal distribution, the standardized characteristic vectors are input to a trained XGboost model, and a corresponding detecting value is output. By means of the method, the problem of personal electrocardiosignal specificity is solved, the method is run at a server end, the pressure on a client is relieved, and the method has higher reference value on N and V type arrhythmias detection results.

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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