Detection and classification method of j-wave based on feature selection of correlation analysis

Abstract

The present invention involves the detection and identification method of J wave, which is specifically selected by the analysis characteristics of the relevant analysis characteristics. This method includes the following steps: ECG signals are prepared by pretreatment, noise and segmentation of the signal;The subsequent signal is decomposed by a three -layer wavelet package, analyzes the third layer coefficient, and calculates the area between the research fragments and the baseline; calculates the cumulative volume characteristics and energy characteristics of the second, third, and fourth levels of the third layer coefficient;The features and energy characteristics are analyzed, and the features are selected according to the classification effect; the features after the selection are used as the input of the support vector machine (SVM) classifier, and the normal signals and J wave signals are classified and identified, and the J -wave signals are successfully detected.The feature selection method of this patent uses correlation analysis is selected to remove the features to remove redundant characteristics and improve the accuracy of classification.

Description

technical field [0001] The invention relates to a method for detecting, identifying and classifying J waves, in particular to a method for detecting and classifying J waves based on correlation analysis feature selection. Background technique [0002] The J point is a sudden turning point at the junction of the QRS complex and the ST segment on the electrocardiogram (ECG), which marks the end of ventricular depolarization and the beginning of repolarization, and the setback after the J point is called the J wave. The general term for malignant arrhythmias, sudden death or other serious cardiovascular diseases caused by J waves is called J wave syndrome. These include Brugada syndrome, idiopathic ventricular fibrillation (VF), hyperacute phase of acute coronary syndrome, and early repolarization syndrome, which can cause malignant arrhythmias, sudden death, or other serious cardiovascular disease. [0003] The electrocardiogram is an important tool to assist doctors in diagn...

AI Technical Summary

Problems solved by technology

[0004] However, in the existing methods for detecting J waves, there may be related features in the extracted features, on the one hand, it will lead to the extension of the time required to analyze the features and train the model; on the other hand, it will produce a "dimension disaster".

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