Electrocardiosignal automatic noise reduction method

Abstract

The invention relates to an electrocardiosignal automatic noise reduction method. The method includes the steps that 1, R-wave peak positions of electrocardiosignals are detected, and preliminary wave filtering is conducted; 2, from the electrocardiosignals after the preliminary wave filtering, cardiac beat segments of a number of continuous cardiac beats are selected, and mean-value calculation is conducted on the cardiac beat segments to obtain a mean template; 3, the mean template is used for replacing the cardiac beat segments corresponding to the obtained electrocardiosignals, and a guide signal is obtained; 4, a number of windows are set in sequence on the guide signal, then in each window, and by adopting a guide wave-filtering model, linear transformation is conducted on the guide signal to obtain wave-filtering output; 5, after linear coefficients of all window are calculated, the linear coefficients are introduced into the guide wave-filtering model, and the value of qi is obtained and serves as a final result. According to the electrocardiosignal automatic noise reduction method, by the adoption of the mean template method, a majority of amplitude features of the electrocardiosignals can be reserved to a certain degree, then, the guide signal is constructed by replacing the main parts of the electrocardiosignals, and in this way, the obtained guide signal reserves most of the amplitude features of the electrocardiosignals.

Description

technical field [0001] The invention relates to an automatic detection and analysis technology of electrocardiographic signals, in particular to an automatic noise reduction method for electrocardiographic signals. Background technique [0002] In recent years, cardiovascular disease has become the number one killer threatening human life and health. Cardiovascular disease is sudden and occurs in an instant. Often because the symptoms are short-lived, the symptoms have disappeared when the patient rushes to the hospital for ECG collection. At this time, the ECG is often difficult to capture effective diagnostic evidence and cannot reflect the actual heart health of the patient because of the lack of ECG data during the onset of the disease. resulting in the inability of patients to receive appropriate treatment. Therefore, the best way to deal with cardiovascular diseases is to conduct 24-hour dynamic ECG monitoring in hospital for cardiovascular patients. Under the socia...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to provide a method for automatic denoising of electrocardiographic signals to...

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