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.