Atrial fibrillation detection method, equipment and device
A detection method and technology of detection devices, which are applied in the directions of diagnostic recording/measurement, medical science, sensors, etc., can solve the problems such as difficulty in meeting demands of accuracy and limited amount of information, achieve strong adaptability, avoid workload and one-sidedness, and improve classification The effect of precision
Active Publication Date: 2019-01-04
深圳市绿航星际太空科技有限公司
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[0005] In view of this, the embodiment of the present application provides a method, device and equipment for detecting atrial fibrillation to solve the problem in the prior art that the accuracy of the heart rhythm variability method is limited by the amount of information, and its accuracy is often difficult to meet the demand
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[0046] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
[0047] In order to illustrate the technical solutions described in this application, specific examples are used below to illustrate.
[0048] Such as figure 1 Shown is a schematic diagram of the implementation flow of the method for detecting atrial fibrillation described in the embodiment of the present application, and is described in detail as follows:
[0049] In step S101, the...
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An atrial fibrillation detection method includes extracting a heartbeat waveform related to an RR interval; performing continuous wavelet transform on the heartbeat waveform to reconstruct a time spectrum tensor of the heartbeat waveform; the trained deep convolution neural network performing feature learning and classification on the time-frequency spectrum system structure of the heartbeat waveform, and obtaining the detection result of the heartbeat waveform. The present application may simultaneously reflect characteristics associated with atrial and ventricular activity, deep convolutionneural network is used to learn and classify the spectrum tensor of heartbeat waveform, which avoids the workload and one-sidedness of traditional methods in feature extraction, and has stronger adaptability to new types of training samples, so it is helpful to improve the classification accuracy.
Description
technical field [0001] The present application belongs to the field of medical equipment, and in particular relates to a detection method, device and equipment for atrial fibrillation. Background technique [0002] Atrial fibrillation (abbreviated as atrial fibrillation) is a kind of cardiac arrhythmia with high incidence (incidence rate is about 1-2%) in the crowd. It not only causes damage to the health of patients, but also increases the risk of stroke, myocardial infarction and other diseases, endangering the lives of patients. The incidence of atrial fibrillation is positively correlated with age, and the incidence rate of people over 75 years old is as high as 10%. With my country's population aging trend, the prevention and treatment of atrial fibrillation will be a severe challenge. [0003] At present, the detection of atrial fibrillation mainly relies on the manual inspection of the electrocardiogram, and its diagnostic accuracy depends on the professional level ...
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IPC IPC(8): A61B5/0402A61B5/046A61B5/361
CPCA61B5/7267A61B5/318A61B5/361
Inventor 张恒贵李钦策刘阳何润南赵娜王宽全
Owner 深圳市绿航星际太空科技有限公司