WEKO3
アイテム
Automatic Classification of Respiratory Sounds Based on Convolutional Recurrent Neural Network and Bagging k-Nearest Neighbor
http://hdl.handle.net/10228/0002001645
http://hdl.handle.net/10228/0002001645d63a723f-f5f3-43eb-8a38-a396a03d265d
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
10450813.pdf (1.4 MB)
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| アイテムタイプ | 共通アイテムタイプ(1) | |||||||||||||||||||
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| 公開日 | 2025-04-24 | |||||||||||||||||||
| タイトル | ||||||||||||||||||||
| タイトル | Automatic Classification of Respiratory Sounds Based on Convolutional Recurrent Neural Network and Bagging k-Nearest Neighbor | |||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 著者 |
Minami, Koki
× Minami, Koki
× 陸, 慧敏
WEKO
15968
× 神谷, 亨
WEKO
402
× Kido, Shoji
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| 著作権関連情報 | ||||||||||||||||||||
| 権利情報Resource | https://creativecommons.org/licenses/by/4.0/ | |||||||||||||||||||
| 権利情報 | Copyright (c) 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC-BY-4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made. | |||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 抄録 | ||||||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||||||
| 内容記述 | Respiratory diseases or lung diseases such as asthma bronchiectasis cystic fibrosis are a serious disease. Approximately 8 million people died in each year by chronic obstructive pulmonary disease, lower respiratory tract infections, trachea, bronchial and lung tumors. In addition, COVID-19 is prevalent worldwide in recent years. To analyze these symptom, auscultation of respiratory sounds is very important for screening the respiratory disease. However, there is no quantitative evaluation method for the diagnosis of respiratory sounds until now. To overcome this problem, it is necessary to develop a system to support the diagnosis of respiratory sounds. In the development of support system for auscultation, research by a large-scale, open database used in ICBHI (The International Conference on Biomedical and Health Informatics) 2017 Challenge is in progress. It is expected that a general purpose and highly accurate system will be developed using this dataset. We describe an algorithm for the automatic classification of the respiratory sounds as crackles, wheeze, both, and normal. We improve the classification rates compared with other ICBHI 2017 Challenge teams based on three components. First, we generate the spectrogram images by short-time Fourier transformation. We also extract features using a convolutional recurrent neural network. Third, we classify unknown respiratory sounds by bagging k-nearest neighbor algorithm. In the experiment, we applied our proposed method to 920 respiratory sound data which is obtained by the ICBHI Challenge data sets, and achieved Sensitivity with 0.670, Specificity with 0.863, ICBHI Score with 0.766 respectively. Also, area under the curve based on receiver operating characteristic curve of normal class with 0.892, crackle with 0.891, wheeze with 0.874, both with 0.883 were obtained respectively. | |||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 書誌情報 |
en : Journal of Image and Graphics 巻 13, 号 1, p. 46-51, 発行日 2025-01-27 |
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| 出版社 | ||||||||||||||||||||
| 出版者 | University of Portsmouth | |||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| キーワード | ||||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||||
| 主題 | respiratory sounds classification | |||||||||||||||||||
| キーワード | ||||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||||
| 主題 | computer aided diagnosis | |||||||||||||||||||
| キーワード | ||||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||||
| 主題 | short-time Fourier transform | |||||||||||||||||||
| キーワード | ||||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||||
| 主題 | convolutional recurrent neural network | |||||||||||||||||||
| キーワード | ||||||||||||||||||||
| 言語 | en | |||||||||||||||||||
| 主題Scheme | Other | |||||||||||||||||||
| 主題 | k-nearest neighbor algorithm | |||||||||||||||||||
| 言語 | ||||||||||||||||||||
| 言語 | eng | |||||||||||||||||||
| 資源タイプ | ||||||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||||||
| 出版タイプ | ||||||||||||||||||||
| 出版タイプ | VoR | |||||||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||||||
| DOI | ||||||||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||||||
| 関連識別子 | https://doi.org/10.18178/joig.13.1.46-51 | |||||||||||||||||||
| ISSN | ||||||||||||||||||||
| 収録物識別子タイプ | PISSN | |||||||||||||||||||
| 収録物識別子 | 2301-3699 | |||||||||||||||||||
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| 収録物識別子タイプ | EISSN | |||||||||||||||||||
| 収録物識別子 | 2972-3973 | |||||||||||||||||||
| 査読の有無 | ||||||||||||||||||||
| 値 | yes | |||||||||||||||||||
| 研究者情報 | ||||||||||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/25_ja.html | |||||||||||||||||||
| 論文ID（連携） | ||||||||||||||||||||
| 値 | 10450813 | |||||||||||||||||||
| 連携ID | ||||||||||||||||||||
| 値 | 14418 | |||||||||||||||||||
