A Few-Shot Learning-Based EEG and Stage Transition Sequence Generator for Improving Sleep Staging Performance

A Few-Shot Learning-Based EEG and Stage Transition Sequence Generator for Improving Sleep Staging Performance

In this study, generative adversarial networks named SleepGAN are proposed to expand the training set for automatic sleep stage classification tasks by generating both electroencephalogram (EEG) epochs and sequence relationships of sleep stages. In order to reach high accuracy, most existing classif...

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Bibliographic Details
Main Authors: Yuyang You, Xiaoyu Guo, Xuyang Zhong, Zhihong Yang
Format: Article
Language:English
Published: MDPI AG 2022-11-01
Series:Biomedicines
Subjects:
few-shot learning
generative adversarial network
single-channel electroencephalogram
sleep stage classification
Online Access:https://www.mdpi.com/2227-9059/10/12/3006

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https://www.mdpi.com/2227-9059/10/12/3006

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