Non-contact atrial fibrillation intelligent detection system based on deep convolution residual network

Abstract

The invention relates to a non-contact atrial fibrillation intelligent detection system based on a deep convolution residual network. Heart impact signals generated during cardiac ejection of the human body can be collected, and whether or not the heart has atrial fibrillation is analyzed by using the deep convolution residual network. The system includes two parts including a heart impact signalcollection part and a deep convolution residual neural network analysis part. The heart impact signal collection part includes a piezoelectric film sensor, a piezoelectric signal processing module, anAD conversion circuit and a processor. Collected data is uploaded to a server running a deep convolution residual network algorithm, and a judgment result is turned back. A deep convolution residualneural network model includes a one-dimensional convolution layer, a downsampling layer, a batch normalization layer, an activation layer and a fully connected layer. A residual structure contained inthe model is formed by adding original signals and deep features extracted after several convolutional sample normalization activation operations. The system can be used for uninterrupted monitoringof the human body at night and give a judgement prompt in time to facilitate timely treatment of disease conditions.

Description

technical field [0001] The invention relates to the fields of artificial intelligence technology and medical monitoring technology, in particular to a non-contact intelligent detection system for atrial fibrillation based on a deep convolutional residual network. Background technique [0002] Atrial fibrillation is a common tachyarrhythmia disease that mostly occurs in people over 60 years old, and the incidence rate doubles with age. Atrial fibrillation is a condition in which the atrium vibrates slightly and cannot contract sufficiently due to irregular and frequent excitation of the atrium. When atrial fibrillation occurs, the pumping volume of the atrium decreases, and the stasis of blood flow is easy to form thrombus, which can increase the incidence of stroke in patients by 5 times, and this risk is still increasing with age. Although the atrium vibrates slightly when atrial fibrillation occurs, the heart function will not decline significantly. Many patients with per...

AI Technical Summary

Problems solved by technology

Diagnosis of atrial fibrillation In addition to various analysis methods based on electrocardiograms, there are also pulse wave detection devices based on PPG or sphygmomanometers, but these devices still require subjects to wear or stick sensors, which are not suitable for long-term monitoring, especially at night , and the single detection time of this type of equipment is short, which is prone to misjudgment

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