An Automatic Discrimination System for Acute Myocardial Infarction Location Based on CNN Neural Network

Abstract

An automatic identification system for acute myocardial infarction positioning based on CNN neural network, which relates to the technical field of myocardial infarction positioning and identification, including a data acquisition system, a cloud platform data storage system, a positioning identification analysis system and a data display system; a wearable ECG monitor and a The person to be judged connects, records and generates a 12-lead original ECG; the ECG acquisition system obtains the 12-lead original ECG data, including the amplitude of the P wave, the amplitude of the QRS complex, the amplitude of the ST segment and the amplitude of the T wave; positioning discriminant analysis The system uses the positioning discrimination model based on the training of the CNN neural network to perform convolution calculation to obtain the discriminant intermediate data, and the discriminant intermediate data is mapped by the sigmoid function to obtain the discrimination result data, so as to make the location discrimination of the acute myocardial infarction occurrence site of the person to be discriminated; this application Provided is an automatic judging system for locating acute myocardial infarction based on CNN neural network, which can accurately judge whether the person to be judged is the site of acute myocardial infarction.

Description

technical field [0001] The invention relates to the technical field of qualitative identification of myocardial infarction, in particular to an automatic identification system for positioning acute myocardial infarction based on a CNN neural network. Background technique [0002] Acute myocardial infarction is myocardial necrosis caused by acute and persistent coronary ischemia and hypoxia. Clinically, there are often severe and persistent substernal pains, which cannot be completely relieved by rest and nitrates, accompanied by increased serum myocardial enzyme activity and progressive ECG changes, which may be complicated by arrhythmia, shock or heart failure, often life-threatening. The disease is most common in Europe and America, and about 1.5 million people in the United States suffer from acute myocardial infarction every year. China has shown a clear upward trend in recent years, with at least 500,000 new cases each year and at least 2 million existing cases, and th...

AI Technical Summary

Problems solved by technology

However, the electrocardiogram equipment currently used in clinical practice cannot accurately and automatically identify changes in the ST segment of the electrocardiogram.

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