An artificial intelligence algorithm model system and method based on dynamic monitoring of cardiac function

Abstract

The invention discloses an artificial intelligence algorithm system and method based on dynamic monitoring and analysis of cardiac function. The artificial intelligence algorithm device includes a data acquisition device, a compressed sensing device, a compressed domain computing device, a preprocessing device and a convolutional neural network. device. The invention is based on an artificial intelligence algorithm model system, which is used in a portable cardiac intelligent patch system, which is worn on the chest wall of the human body in the form of a wearable device to monitor the mechanical vibration of the heart in vitro, and obtain the vibration of the heart continuously and non-invasively in real time. Information, combined with digital processing, machine learning and artificial intelligence technology, pattern recognition and intelligent diagnosis, early detection of cardiac physical structure and rhythm abnormalities, such as valve disease, abnormal movement of the heart wall, changes in cardiac ejection fraction, arrhythmias, etc. To achieve the purpose of early warning and timely medical care of heart disease. It has practical significance for early warning monitoring of cardiac function, rehabilitation monitoring after surgery, and daily monitoring of home-based elderly and sports people.

Description

technical field [0001] The invention belongs to the technical field of intelligent medical devices, and in particular relates to an artificial intelligence algorithm model system and method based on dynamic monitoring of cardiac function. Background technique [0002] Heart disease is the number one killer of humanity, and today billions of people with heart disease worldwide need timely, appropriate and affordable medical care. The traditional electrocardiogram (ECG) can only detect abnormal ECG signals, but it has little or no effect on the defects, lesions, aging, and functional loss of the physical structure of the heart itself (such as partial myocardial necrosis). Detection methods such as echocardiography, computed tomography (CT), magnetic resonance imaging (MRI) and myocardial perfusion radionuclide scanning require large-scale equipment and professional operation, the detection cost is high, and it is difficult to monitor anytime, anywhere, and lose valuable pathol...

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

Images