J wave detection and classification method based on correlation analysis characteristic selection

A technology of correlation analysis and feature selection, which is applied in pattern recognition in signals, instrument, character and pattern recognition, etc., can solve the problems of analysis feature training model time extension, dimension disaster, etc., and achieve the effect of improving classification accuracy

Active Publication Date: 2017-03-15
TAIYUAN UNIV OF TECH
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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

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  • J wave detection and classification method based on correlation analysis characteristic selection
  • J wave detection and classification method based on correlation analysis characteristic selection

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Embodiment Construction

[0017] The J-wave detection and classification method based on correlation analysis feature selection comprises the following steps:

[0018] A number of ECG signals are obtained from the electrocardiograph. The ECG signals include normal ECG signals and J wave signals. The ECG signals are divided into training group signals and test group signals. After preprocessing the ECG signals, denoise and segment the ECG signals ;

[0019] Carry out three-layer wavelet packet decomposition on the segmented ECG signal, analyze the third-layer decomposition coefficients, and calculate the 2nd, 3rd, and 4th-order cumulant features of the third-layer decomposition coefficients. Wavelet packet transform (WPT) is a wavelet transform ( The extension of WT), the basic idea is to concentrate information energy, find order in details, filter out the laws, and provide a more refined analysis method for signals. Wavelet transform only decomposes the low-frequency approximate coefficients of the s...

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Abstract

The invention relates to a detection, recognition and classification method for a J wave, specifically a J wave detection and classification method based on correlation analysis characteristic selection. The method comprises the following steps: carrying out the preprocessing of an ECG signal, and carrying out the denoising and segmenting of the signal; carrying out three-layer wavelet packet decomposition of the segmented signal, carrying out the analysis of a third-layer coefficient, and calculating the area between a research segment and a base line; calculating the second-order, third-order and fourth-order cumulant characteristics and energy characteristics of the third-layer coefficient; carrying out the correlation analysis of the cumulant characteristics and energy characteristics, and carrying out the characteristic selection according to a classification effect; employing the selected characteristics as the input of an SVM (support vector machine) classifier, carrying out the classification and recognition of a normal signal and a J-wave signal, and successfully detecting the J-wave signal. According to the invention, a correlation analysis characteristic selection method is used for characteristic screening, thereby removing the redundant characteristics and improving the classification accuracy.

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...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F2218/02G06F2218/12
Inventor 李灯熬赵菊敏牛慧颖
Owner TAIYUAN UNIV OF TECH
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