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Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds

  • Published:2019-09 Issue: Volume:178 Page:19-30
  • ISSN:0169-2607
  • Container-title:Computer Methods and Programs in Biomedicine
  • language:en
  • Short-container-title:Computer Methods and Programs in Biomedicine

Author:

JIANG Dihong,MA Yu,WANG Yuanyuan

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Cited by 24 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. Efficient Sleep Stage Identification Using Piecewise Linear EEG Signal Reduction: A Novel Algorithm for Sleep Disorder Diagnosis;Sensors;2024-08-14

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

3. A Hierarchical Neural Network on Riemannian Manifold and Convolutional Neural Network for Sleep Stage Classification;2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA);2024-06-26

4. Multivariate phase space reconstruction and Riemannian manifold for sleep stage classification;Biomedical Signal Processing and Control;2024-02

5. Self-superviesed sleep staging model based on contrast learing;3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023);2023-07-21
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