Art

J-GLOBAL ID：202202280842318665   Reference number：22A2959830

Sleep Apnea Classification Algorithm Development Using a Machine-Learning Framework and Bag-of-Features Derived from Electrocardiogram Spectrograms

心電図スペクトログラムに由来する機械学習フレームワークとバッグオブ特徴を用いた睡眠時無呼吸分類アルゴリズムの開発【JST・京大機械翻訳】

Author (9)： Lin Cheng-Yu (Department of Otolaryngology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan) ,  Lin Cheng-Yu (Department of Environmental and Occupational Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan) ,  Lin Cheng-Yu (Sleep Medicine Center, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 704, Taiwan) ,  Wang Yi-Wen (Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan 701, Taiwan) ,  Setiawan Febryan (Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan 701, Taiwan) ,  Trang Nguyen Thi Hoang (Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan 701, Taiwan) ,  Lin Che-Wei (Department of Biomedical Engineering, College of Engineering, National Cheng Kung University, Tainan 701, Taiwan) ,  Lin Che-Wei (Medical Device Innovation Center, National Cheng Kung University, Tainan 704, Taiwan) ,  Lin Che-Wei (Institute of Gerontology, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan)
Material： Journal of Clinical Medicine (Web)
Volume： 11  Issue： 1  Page： 192  Publication year： 2021 
JST Material Number： U7214A  ISSN： 2077-0383  Document type： Article
Article type： 原著論文  Country of issue： Switzerland (CHE)  Language： ENGLISH (EN)

Abstract/Point： Background: Heart rate variabi...

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Thesaurus term： *algorithm ,  noise(signal) ,  *electrocardiogram ,  *respiration ,  *sleep ,  frequency band ,  artifact ,  *machine learning ,  university hospital ,  support vector machine
Semi thesaurus term： 被験者 ,  アンサンブル学習 ,  *分類アルゴリズム ,  *スペクトログラム ,  検出アルゴリズム , 【Automatic Indexing@JST】

Author keywords (6)： sleep apnea ,  time-frequency transformation ,  bag-of-features ,  support vector machine ,  k-nearest neighbor algorithm ,  ensemble learning

JST classification (2)： Biometry  (EL03020C) ,  Respiratory system diagnosis  (GI02000S)

Reference (49)：

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• American Academy of Sleep Medicine. Hidden health crisis costing America billions. In Underdiagnosing and Undertreating Obstructive Sleep Apnea Draining Healthcare System; Frost & Sullivan: Mountain View, CA, USA, 2016.
• Facco, F.L.; Lopata, V.; Wolsk, J.M.; Patel, S.; Wisniewski, S.R. Can We Use Home Sleep Testing for the Evaluation of Sleep Apnea in Obese Pregnant Women? Sleep Disord. 2019, 2019, 3827579.
• Dalewski, B.; Kamińska, A.; Syrico, A.; Kałdunska, A.; Pałka, Ł.; Sobolewska, E. The Usefulness of Modified Mallampati Score and CT Upper Airway Volume Measurements in Diagnosing OSA among Patients with Breathing-Related Sleep Disorders. Appl. Sci. 2021, 11, 3764.
• Philip, P.; Bailly, S.; Benmerad, M.; Micoulaud-Franchi, J.; Grillet, Y.; Sapène, M.; Jullian-Desayes, I.; Joyeux-Faure, M.; Tamisier, R.; Pépin, J. Self-reported sleepiness and not the apnoea hypopnoea index is the best predictor of sleepiness-related accidents in obstructive sleep apnoea. Sci. Rep. 2020, 10, 16267.

Terms in the title (8)： 心電図 ,  スペクトログラム ,  機械学習 ,  フレームワーク ,  バッグ ,  睡眠時無呼吸 ,  分類アルゴリズム ,  開発