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Coronary heart disease electrocardiogram screening system and method based on residual neural network

A neural network and electrocardiogram technology, used in medical science, diagnostic signal processing, sensors, etc., can solve the problems of inability to process structured data, insufficient model accuracy, insufficient scalability and scalability, and achieve good scalability and practicality. Strong and accurate effect

Active Publication Date: 2021-07-30
SHANGHAI JIAOTONG UNIV
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  • Abstract
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AI Technical Summary

Problems solved by technology

Although the existing technology based on the ECG feature extraction based on the deep learning algorithm has improved the corresponding accuracy and diversity, the shortcomings of the existing technology are that it cannot handle structured data, the accuracy of the model is not enough, and the scalability and extension Insufficient performance

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  • Coronary heart disease electrocardiogram screening system and method based on residual neural network
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  • Coronary heart disease electrocardiogram screening system and method based on residual neural network

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Embodiment Construction

[0036] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0037] A kind of coronary heart disease electrocardiogram screening system based on residual neural network provided by the present invention comprises:

[0038] ECG signal processing module: extract the ECG signal generated by the ECG machine, use symlets4 wavelet to perform multi-layer decomposition and denoising of the ECG signal, find the position of the R wave in the ECG sequence data converted from the ECG signal, and use it as a reference Heart beat split. The present invention uses a large amou...

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Abstract

The invention provides a coronary heart disease electrocardiogram screening system based on a residual neural network, and the system comprises an electrocardiosignal processing module which is used for extracting electrocardiosignals generated by an electrocardiograph, carrying out the multi-layer decomposition and noise reduction of the electrocardiosignals through employing a symlets4 wavelet, searching the position of an R wave in electrocardiosignal sequence data converted from the electrocardiosignals, and carrying out the heart beat segmentation based on the position of the R wave; a depth feature extraction module which is used for performing translation and scaling on the data processed by the electrocardiosignal processing module to enhance the data, and extracting the depth features of the twelve-lead electrocardiogram by using a ResneXt50 network comprising an extrusion and excitation network module; and a tree model prediction module which is used for combining the depth features extracted by the depth feature extraction module with electrocardiograph data, and inputting the trained XGBoost model to obtain the prediction probability of the coronary heart disease electrocardio features in the electrocardiogram. The system is low in installation and use cost, can achieve automatic screening, is higher in accuracy compared with diagnosis of an electrocardiograph, can reduce misjudgment or missed judgment, and reduces the workload of doctors.

Description

technical field [0001] The invention relates to the technical field of cardiovascular disease diagnosis, in particular to a residual neural network-based ECG screening system and method for coronary heart disease. Background technique [0002] Coronary atherosclerotic heart disease, referred to as coronary heart disease, refers to ischemic and hypoxic heart disease caused by coronary atherosclerosis and coronary artery stenosis, and arrhythmia is a common complication. Coronary heart disease is one of the important causes of death in the elderly, and the incidence rate is proportional to age. Clinically, it manifests as angina pectoris, myocardial infarction and other conditions, and even death due to arrhythmia and heart failure. At present, the gold standard for diagnosing coronary heart disease is coronary angiography, but because of its high cost and certain risks, it cannot be popularized. At present, the use of 12-lead ECG to detect coronary heart disease is a very i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/352A61B5/355A61B5/349
CPCA61B5/72A61B5/7275A61B5/726A61B5/7203A61B5/7221
Inventor 骆源雷锐侯旭宏贾伟平
Owner SHANGHAI JIAOTONG UNIV
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