MixSleepNet: A Multi-Type Convolution Combined Sleep Stage Classification Model-Reference-Cited by-同舟云学术

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MixSleepNet: A Multi-Type Convolution Combined Sleep Stage Classification Model

Published:2024-02 Issue: Volume:244 Page:107992
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Ji Xiaopeng^ORCID,Li Yan^ORCID,Wen Peng^ORCID,Barua Prabal,Acharya U Rajendra

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference67 articles.

1. Circuit-based interrogation of sleep control;Weber;Nature,2016

2. Classification and epidemiology of sleep disorders;Ivanenko;Child Adolesc. Psychiatr. Clin.,2009

3. A new method for automatic sleep stage classification;Zhang;IEEE Trans. Biomed. Circuits Syst.,2017

4. Discriminating the brain activities for brain–computer interface applications through the optimal allocation-based approach;Siuly;Neural Comput. Appl.,2015

5. The AASM manual for the scoring of sleep and associated events;Berry;Rules Terminol. Tech. Specif. Darien Ill. Am. Acad. Sleep Med.,2012

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. SleepGCN: A transition rule learning model based on Graph Convolutional Network for sleep staging;Computer Methods and Programs in Biomedicine;2024-12

2. A review of automated sleep stage based on EEG signals;Biocybernetics and Biomedical Engineering;2024-07

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