Convolutional neural network information processing system based on cardiac function monitoring and training method

Abstract

The invention discloses a convolutional neural network information processing system and method based on cardiac function dynamic monitoring. The convolutional neural network information processing system comprises a 14-layer efficient convolutional neural network. The convolutional neural network information processing technology is applied to a portable heart intelligent patch system, and is worn on the chest wall of a human body in the form of wearable equipment For monitoring mechanical vibration of the heart in vitro and obtaining vibration information of the heart continuously in real time in a non-invasive mode, and by combining digital processing, machine learning and artificial intelligence technical mode recognition and intelligent diagnosis, the convolutional neural network information processing technology can find physical structure and pulsation rhythm abnormalities such as valvular lesion, abnormal movement of the heart wall, heart ejection fraction change and arrhythmiaof the heart in the early stage. And by combining an early warning report system, the convolutional neural network information processing technology can achieve the purposes of early warning of heartdiseases and timely medical care. The convolutional neural network information processing technology is of great significance to early warning and monitoring of severe arrhythmia, angina pectoris andacute myocardial infarction, rehabilitation monitoring after a contrast operation, daily monitoring of home-based care people and sports people.

Description

technical field [0001] The invention belongs to the technical field of intelligent medical devices, and in particular relates to a convolutional neural network information processing system and training method based on dynamic monitoring and analysis of cardiac function. Background technique [0002] Heart disease is the number one killer of human beings, and there are billions of heart patients worldwide today who need timely, appropriate and affordable medical care. The traditional electrocardiogram (ECG) can only detect abnormal ECG signals, but has little or no effect on the defects, lesions, aging, and loss of function of the physical structure of the heart itself (such as partial necrosis of the myocardium). Echocardiography, computed tomography (CT), magnetic resonance imaging (MRI) and myocardial perfusion nuclide scanning require large-scale equipment and professional personnel to operate, and the cost of detection is high, and it is difficult to monitor anytime and...

AI Technical Summary

Problems solved by technology

[0006] To sum up, the existing technologies and products exist: firstly, data analysis processing and disease diagnosis rely on cloud platform or offline computer equipment, which has poor real-time performance, affects the practicability of immediate response and immediate disposal, and low data availability

The second is that the supporting wearable device has a complex structure, high cost and inconvenient use

The third is that the software algorithm model is simple, resulting in weak disease diagnosis ability

Fourth, data security issues are not considered; fifth, commercial service models such as cardiac early warning, surgical rehabilitation, and home care for the elderly are not considered

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