Arrhythmia classification method based on multi-feature fusion and Stacking-DWKNN

A multi-feature fusion and arrhythmia technology, applied in medical science, diagnosis, diagnostic recording/measurement, etc., can solve problems such as time-consuming, impractical, ECG signal shape and time feature differences, and achieve the goal of improving the accuracy of results Effect

Active Publication Date: 2020-08-21
ZHENGZHOU UNIV
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Problems solved by technology

However, under different conditions, there are significant differences in the morphology and temporal characteristics of ECG signals, and some arrhythmias only occasionally occur in patients' daily life, requiring the use of dynamic electrocardiography to record long-term ECG activity
Traditional Holter analysis is done manually, but manual beat-by-beat manual analysis of long-term ECGs is time-consuming and impractical

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  • Arrhythmia classification method based on multi-feature fusion and Stacking-DWKNN
  • Arrhythmia classification method based on multi-feature fusion and Stacking-DWKNN
  • Arrhythmia classification method based on multi-feature fusion and Stacking-DWKNN

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Embodiment Construction

[0030] The technical solutions in the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Apparently, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0031] A kind of arrhythmia classification method based on multi-feature fusion and Stacking-DWKNN, comprises the following steps:

[0032] S1, using continuous wavelet transformation to remove noise in the ECG signal;

[0033] S2. Segment and intercept the ECG signal processed in step S1 to obtain a complete heartbeat, then perform feature extraction from the intercepted heartbeat, and establish the following data sets according to the categories of the extracted features:

[0034] Set A = {2...

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Abstract

The invention relates to an arrhythmia classification method based on multi-feature fusion and Stacking-DWKNN. The arrhythmia classification method comprises the following steps: S1, removing noise inan electrocardiosignal by adopting continuous wavelet transform; S2, segmenting the electrocardiosignal processed in the step S1 to intercept a complete heart beat, then performing feature extractionon the intercepted heart beat, and establishing the following data sets for the extracted features according to categories, wherein the set A = {235 single heart beat morphological characteristics},the set B = {P-QRS-T wave}, the set C = {PR interval}, the set D = {QT interval}, the set E = {ST segment}, the set F = {RR interval}, the set G = {R amplitude}, and the set H = {T amplitude}; S3, inputting any one set or a combination of any multiple sets in the data set in the step S2 into a plurality of KNN algorithms which are integrated by Stacking and improved by weight values for heart beatclassification. The heart beat classification method provided by the invention can effectively improve the result accuracy of heart beat classification.

Description

technical field [0001] The invention belongs to the technical field of arrhythmia classification methods, and is an arrhythmia classification method based on multi-feature fusion and Stacking-DWKNN. Background technique [0002] The electrocardiogram (ECG) is a non-invasive, inexpensive and well-established diagnostic tool that is widely used in a variety of applications. It represents changes in the electrical activity of the heart over time and contains basic physiological information widely used to analyze cardiac function, which is important for the detection of cardiac arrhythmias. Most arrhythmias are harmless, but some can be life-threatening immediately. Therefore, accurate detection of cardiac arrhythmias in patients plays a vital role in the prevention of cardiovascular diseases. The electrocardiogram (ECG) has the advantages of easy acquisition and low equipment cost, and can be used to judge whether the arrhythmia is sinus or ectopic, and is an important basis ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0402A61B5/0452
CPCA61B5/7203A61B5/726A61B5/7267A61B5/349A61B5/318
Inventor 李润川冀沙沙申圣亚王宗敏周兵
Owner ZHENGZHOU UNIV
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