CHMMConvScaleNet: a hybrid convolutional neural network and continuous hidden Markov model with multi-scale features for sleep posture detection.

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Title: CHMMConvScaleNet: a hybrid convolutional neural network and continuous hidden Markov model with multi-scale features for sleep posture detection.
Authors: Hu D; School of Information and Communication Engineering, Institute for Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, China., Gao W; School of Information and Communication Engineering, Institute for Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, China. gaoweidong@bupt.edu.cn., Ang KK; Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, 138632, Singapore.; College of Computing and Data Science, Nanyang Technological University, Singapore, 639798, Singapore., Hu M; Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, 138632, Singapore., Huang R; Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Beijing, 100730, China. huangrong0212@163.com., Chuai G; School of Information and Communication Engineering, Institute for Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, China., Li X; Vaccination Clinic of Zhaoyuan Mengzhi Sub District Community Health Service Center, Shandong, 265400, China.
Source: Scientific reports [Sci Rep] 2025 Apr 10; Vol. 15 (1), pp. 12206. Date of Electronic Publication: 2025 Apr 10.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Hu+D%22">Hu D</searchLink>; School of Information and Communication Engineering, Institute for Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, China.<br /><searchLink fieldCode="AU" term="%22Gao+W%22">Gao W</searchLink>; School of Information and Communication Engineering, Institute for Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, China. gaoweidong@bupt.edu.cn.<br /><searchLink fieldCode="AU" term="%22Ang+KK%22">Ang KK</searchLink>; Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, 138632, Singapore.; College of Computing and Data Science, Nanyang Technological University, Singapore, 639798, Singapore.<br /><searchLink fieldCode="AU" term="%22Hu+M%22">Hu M</searchLink>; Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, 138632, Singapore.<br /><searchLink fieldCode="AU" term="%22Huang+R%22">Huang R</searchLink>; Department of Respiratory and Critical Care Medicine, Peking Union Medical College Hospital, Beijing, 100730, China. huangrong0212@163.com.<br /><searchLink fieldCode="AU" term="%22Chuai+G%22">Chuai G</searchLink>; School of Information and Communication Engineering, Institute for Beijing University of Posts and Telecommunications (BUPT), Beijing, 100876, China.<br /><searchLink fieldCode="AU" term="%22Li+X%22">Li X</searchLink>; Vaccination Clinic of Zhaoyuan Mengzhi Sub District Community Health Service Center, Shandong, 265400, China.
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  Data: <searchLink fieldCode="JN" term="%22101563288%22">Scientific reports</searchLink> [Sci Rep] 2025 Apr 10; Vol. 15 (1), pp. 12206. <i>Date of Electronic Publication: </i>2025 Apr 10.
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        Value: 10.1038/s41598-025-93541-0
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              Text: 2025 Apr 10
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