Tao, Y., Yang, Y., Yang, P. orcid.org/0000-0002-8553-7127 et al. (4 more authors) (2023) A novel feature relearning method for automatic sleep staging based on single-channel EEG. Complex & Intelligent Systems, 9 (1). pp. 41-50. ISSN 2199-4536
Abstract
Correctly identifying sleep stages is essential for assessing sleep quality and treating sleep disorders. However, the current sleep staging methods have the following problems: (1) Manual or semi-automatic extraction of features requires professional knowledge, which is time-consuming and laborious. (2) Due to the similarity of stage features, it is necessary to strengthen the learning of features. (3) Acquisition of a variety of data has high requirements on equipment. Therefore, this paper proposes a novel feature relearning method for automatic sleep staging based on single-channel electroencephalography (EEG) to solve these three problems. Specifically, we design a bottom–up and top–down network and use the attention mechanism to learn EEG information fully. The cascading step with an imbalanced strategy is used to further improve the overall classification performance and realize automatic sleep classification. The experimental results on the public dataset Sleep-EDF show that the proposed method is advanced. The results show that the proposed method outperforms the state-of-the-art methods. The code and supplementary materials are available at GitHub: https://github.com/raintyj/A-novel-feature-relearning-method.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | Sleep staging; Automatic; Single channel; Attention; Imbalanced strategy |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Sep 2022 09:57 |
Last Modified: | 28 Feb 2023 17:19 |
Status: | Published |
Publisher: | Springer Nature |
Refereed: | Yes |
Identification Number: | 10.1007/s40747-022-00779-6 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:190515 |