Method for classifying imbalance heart beats based on multi-module neural network
A technology of neural network and classification method, which is applied in the field of electrocardiogram classification to achieve the effect of improving classification accuracy
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[0024] Below in conjunction with accompanying drawing, the present invention will be further described.
[0025] The overall process of the present invention is as figure 1 shown. The overall process includes the following modules: ECG signal preprocessing module, unbalanced data processing module, feature extraction and classification module. In the preprocessing module, the noise in the original ECG signal is removed, and it is divided into cardiac beat segments of equal length; the unbalanced data processing module is the core of the whole system, which combines the nature of the ECG signal itself and the algorithm Features, a series of data and algorithm processing are performed on the unbalanced heart beat data; finally, the processed heart beat data is input to the convolutional neural network for feature extraction and classification. The specific implementation steps are as follows.
[0026] 1. ECG signal preprocessing module
[0027] Due to the influence of the ac...
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