Electrocardiosignal atrial fibrillation detection method based on one-dimensional dense connection convolutional network

Abstract

The invention discloses an electrocardiosignal atrial fibrillation detection method based on a one-dimensional dense connection convolutional network. The method comprises the following steps: step 1,acquiring a plurality of electrocardiosignal segments containing atrial fibrillation labels; 2, preprocessing the electrocardiosignal segments in the step 1 and taking the electrocardiosignal segments as training data for training a one-dimensional dense connection convolutional network model; 3, building the one-dimensional dense connection convolutional network model by utilizing a deep learning framework; 4, randomly selecting the size of an initial parameter, continuously sending the training data to the model in batches, and performing back propagation to update the network parameter toobtain an optimal parameter; 5, carrying out lightweight processing on the trained network, wherein the lightweight processing comprises parameter quantification and network pruning; and 6, collectingelectrocardiosignals of the patient, sending the signal waveform as input into the one-dimensional dense connection convolutional network model, outputting a result, and pre-judging whether the patient has atrial fibrillation or not.

Description

technical field [0001] The invention relates to a method for detecting electrocardiographic signal atrial fibrillation. Background technique [0002] Atrial fibrillation is a very common clinical arrhythmia symptom, often manifested as rapid and irregular atrial activation, resulting in loss of effective atrial systolic function. Atrial fibrillation has a high incidence rate in the population, and is often accompanied by diseases such as heart failure, senile dementia and stroke, which seriously threaten people's life safety. Therefore, early detection of atrial fibrillation is of great significance for patients to obtain targeted treatment. The ECG signal in a normal cardiac cycle is composed of P wave, QRS wave group and T wave, which respectively represent the depolarization and excitation of the corresponding parts. Atrial fibrillation is the disappearance of P waves due to irregular atrial activation, replaced by some irregular F waves, and the R-R interval also appea...

AI Technical Summary

Problems solved by technology

The invention also has end-to-end features, can directly input ECG signals to obtain classification results, and solves the problem that the traditional method divides the detection process into multiple steps

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