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Classification between normal and abnormal respiratory sounds based on maximum likelihood approach
http://hdl.handle.net/10069/22321
http://hdl.handle.net/10069/223219934902a-e4e2-4335-8f12-72b109151379
名前 / ファイル | ライセンス | アクション |
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ICASSP2009_517.pdf (196.8 kB)
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Item type | 会議発表論文 / Conference Paper(1) | |||||
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公開日 | 2009-11-05 | |||||
タイトル | ||||||
タイトル | Classification between normal and abnormal respiratory sounds based on maximum likelihood approach | |||||
言語 | ||||||
言語 | eng | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Acoustic signal detection | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Biomedical acoustics | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Lung sounds | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Pattern classification | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||
資源タイプ | conference paper | |||||
著者 |
Matsunaga, Shoichi
× Matsunaga, Shoichi× Yamauchi, Katsuya× Yamashita, Masaru× Miyahara, Sueharu |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | In this paper, we have proposed a novel classification procedure for distinguishing between normal respiratory and abnormal respiratory sounds based on a maximum likelihood approach using hidden Markov models. We have assumed that each inspiratory/expiratory period consists of a time sequence of characteristic acoustic segments. The classification procedure detects the segment sequence with the highest likelihood and yields the classification result. We have proposed two elaborate acoustic modeling methods: one method is individual modeling for adventitious sound periods and for breath sound periods for the detection of abnormal respiratory sounds, and the other is a microphone-dependent modeling method for the detection of normal respiratory sounds. Classification experiments conducted using the former method revealed that this method demonstrated an increase of 19.1% in its recall rate of abnormal respiratory sounds as compared with the recall rate of a baseline method. It has also been revealed that the latter modeling method demonstrates an increase in its recall rate for the detection of not only normal respiratory sounds but also for abnormal respiratory sounds. These experimental results have confirmed the validity of our proposed classification procedure. | |||||
内容記述 | ||||||
内容記述タイプ | Other | |||||
内容記述 | ICASSP 2009 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing : Taipei, Taiwan, 2009.04.19-2009.04.24 | |||||
書誌情報 |
2009 IEEE International Conference on Acoustics, Speech and Signal Processing p. 517-520, 発行日 2009-04 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 07367791 | |||||
ISBN | ||||||
識別子タイプ | ISBN | |||||
関連識別子 | 978-1-4244-2353-8 | |||||
DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1109/ICASSP.2009.4959634 | |||||
権利 | ||||||
権利情報 | c2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
出版者 | ||||||
出版者 | IEEE | |||||
引用 | ||||||
内容記述タイプ | Other | |||||
内容記述 | 2009 IEEE International Conference on Acoustics, Speech and Signal Processing, pp.517-520; 2009 |