Atrial fibrillation signal recognition method, apparatus and device

An atrial fibrillation signal recognition method, wherein the method comprises:

• obtaining an electrocardiogram signal to be recognized;
• and
• inputting the electrocardiogram signal to be recognized to a pre-established atrial fibrillation signal recognition model, and outputting an atrial fibrillation signal recognition result, wherein
• the atrial fibrillation signal recognition model is established in the following way:
• obtaining a specified number of electrocardiogram sample signals and corresponding identifier information, wherein the identifier information comprises identifier information of normal signals and of atrial fibrillation signals;
• balancing, according to the number of normal signals, the atrial fibrillation signals by means of synthetic minority oversampling technique (SMOTE);
• establishing a network structure of multiple convolutional neural networks, each of the convolutional neural networks being provided with a specific receptive field for recognizing the atrial fibrillation signals of a corresponding granularity;
• and
• inputting the normal signals and the balanced atrial fibrillation signals to the network structure for training, to generate the atrial fibrillation signal recognition model;
• wherein the network structure of multiple convolutional neural networks comprises a first network and a second network;
• both the first network and the second network are VGG-16 convolutional neural networks;
• each of the first network and the second network comprises multiple convolutional lavers and multiple max-pooling layers;
• a receptive field of a convolution kernel in the first network is less than or equal to a receptive field of a convolution kernel in the second network;
• max-pooling lavers of the last layers of the first network and the second network are connected to each other;
• the interconnected max-pooling layers are further successively connected to multiple fully connected layers and a Softmax layer.