Exploring Structure Incentive Domain Adversarial Learning for Generalizable Sleep Stage Classification
文献类型：期刊论文
| 作者 | Ma, Shuo1; Zhang, Yingwei2; Chen, Yiqiang2; Xie, Tao3; Song, Shuchao1; Jia, Ziyu4
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| 刊名 | ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
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| 出版日期 | 2024 |
| 卷号 | 15期号:1页码:30 |
| 关键词 | physiological signal time-series signal sleep stage classification domain generalization subject independent |
| ISSN号 | 2157-6904 |
| DOI | 10.1145/3625238 |
| 通讯作者 | Chen, Yiqiang(yqchen@ict.ac.cn) |
| 英文摘要 | Sleep stage classification is crucial for sleep state monitoring and health interventions. In accordance with the standards prescribed by the American Academy of Sleep Medicine, a sleep episode follows a specific structure comprising five distinctive sleep stages that collectively form a sleep cycle. Typically, this cycle repeats about five times, providing an insightful portrayal of the subject's physiological attributes. The progress of deep learning and advanced domain generalization methods allows automatic and even adaptive sleep stage classification. However, applying models trained with visible subject data to invisible subject data remains challenging due to significant individual differences among subjects. Motivated by the periodic categorycomplete structure of sleep stage classification, we propose a Structure Incentive Domain Adversarial learning (SIDA) method that combines the sleep stage classification method with domain generalization to enable cross-subject sleep stage classification. SIDA includes individual domain discriminators for each sleep stage category to decouple subject dependence differences among different categories and fine-grained learning of domain-invariant features. Furthermore, SIDA directly connects the label classifier and domain discriminators to promote the training process. Experiments on three benchmark sleep stage classification datasets demonstrate that the proposed SIDA method outperforms other state-of-the-art sleep stage classification and domain generalization methods and achieves the best cross-subject sleep stage classification results. |
| 资助项目 | National Key Research and Development Plan of China[2021YFC2501202] ; National Natural Science Foundation of China[61972383] ; National Natural Science Foundation of China[62302487] ; Beijing Municipal Science & Technology Commission[Z221100002722009] ; Innovative Research Program of Shandong Academy of Intelligent Computing Technology[SDAICT2191010] ; National Heart, Lung, and Blood Institute[R24 HL114473] ; National Heart, Lung, and Blood Institute[75N92019R002] ; National Heart, Lung, and Blood Institute[U01HL53916] ; National Heart, Lung, and Blood Institute[U01HL53931] ; National Heart, Lung, and Blood Institute[U01HL53934] ; National Heart, Lung, and Blood Institute[U01HL53937] ; National Heart, Lung, and Blood Institute[U01HL64360] ; National Heart, Lung, and Blood Institute[U01HL53938] ; National Heart, Lung, and Blood Institute[U01HL53940] ; National Heart, Lung, and Blood Institute[U01HL53941] ; National Heart, Lung, and Blood Institute[U01HL63463] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001170039400014 |
| 出版者 | ASSOC COMPUTING MACHINERY |
| 资助机构 | National Key Research and Development Plan of China ; National Natural Science Foundation of China ; Beijing Municipal Science & Technology Commission ; Innovative Research Program of Shandong Academy of Intelligent Computing Technology ; National Heart, Lung, and Blood Institute |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58351]  |
| 专题 | 自动化研究所_脑网络组研究中心 |
| 通讯作者 | Chen, Yiqiang |
| 作者单位 | 1.Chinese Acad Sci, Univ Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Devices, Beijing, Peoples R China 2.Chinese Acad Sci, Univ Chinese Acad Sci,Inst Comp Technol, Shangdong Acad Intelligent Comp Technol, Beijing Key Lab Mobile Comp & Pervas Devices, Beijing, Peoples R China 3.NIO, Beijing, Peoples R China 4.Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ma, Shuo,Zhang, Yingwei,Chen, Yiqiang,et al. Exploring Structure Incentive Domain Adversarial Learning for Generalizable Sleep Stage Classification[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2024,15(1):30. |
| APA | Ma, Shuo,Zhang, Yingwei,Chen, Yiqiang,Xie, Tao,Song, Shuchao,&Jia, Ziyu.(2024).Exploring Structure Incentive Domain Adversarial Learning for Generalizable Sleep Stage Classification.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,15(1),30. |
| MLA | Ma, Shuo,et al."Exploring Structure Incentive Domain Adversarial Learning for Generalizable Sleep Stage Classification".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 15.1(2024):30. |
入库方式： OAI收割
来源：自动化研究所
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