Unbalanced heart rate data set processing method and system based on generative adversarial network
The invention belongs to the technical field of medical data processing, and discloses an unbalanced heart rate data set processing method and system based on a generative adversarial network. According to the method, a multilayer wavelet transform decomposition method is adopted, baseline drift and...
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Main Authors | , , , , , , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
03.05.2024
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Subjects | |
Online Access | Get full text |
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Summary: | The invention belongs to the technical field of medical data processing, and discloses an unbalanced heart rate data set processing method and system based on a generative adversarial network. According to the method, a multilayer wavelet transform decomposition method is adopted, baseline drift and noise of heart rate signals are filtered out, and heart rate data are converted from one-dimensional data to low-latitude representation data; performing reversible mapping on high-dimensional data and low-dimensional representation data of the electrocardiosignals by using the constructed CECG-GAN neural network model, and training the CECG-GAN neural network model to obtain a synthetic data set for expanding scarce samples; and judging whether the obtained synthetic data set is an effective sample or not by combining the accuracy rate, the recall rate and the F1-score value of the classification judgment model, and storing the effective sample. The high synthesis quality and diversity of the CECG-GAN neural netw |
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Bibliography: | Application Number: CN202410381182 |