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Paper Abstract and Keywords
Presentation 2014-05-22 16:20
Signal Processing for Lung-Sound Recognition -- Separation and Classification of Continuous and Discontinuous Adventitious Sounds --
Tomoya Sakai, Takahiro Uchida, Aeri Sakaguchi, Senya Kiyasu (Nagasaki Univ.), Sueharu Miyahara (formerly Nagasaki Univ.), Mikio Oka (Kawasaki Med. Sch.) SIP2014-11 IE2014-11 PRMU2014-11 MI2014-11
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents signal separation techniques for pattern recognition of lung sounds. From a viewpoint of pattern recognition, pulmonary auscultation is essentially a multi-label classification problem where all lung-sound components are to be predicted for an auscultatory sound. An auscultatory sound acquired from a patient with pulmonary disorder may be composed of multiple types of adventitious (abnormal) sounds as well as breath. The present approach decomposes the auscultatory sound into components without explicitly modeling them. Robust principal component analysis is applied to the sound spectrogram to yield sound components with low-rank and sparse spectrograms. It is experimentally shown that continuous adventitious sound component is obtained from the sparse spectrogram. Coarse and fine crackles can be extracted and classified by sparse representation of the sound component from the low-rank spectrogram.
Keyword (in Japanese) (See Japanese page) 
(in English) Respiratory system diagnosis / Electronic auscultation / Signal separation / Robust PCA / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 39, SIP2014-11, pp. 55-60, May 2014.
Paper # SIP2014-11 
Date of Issue 2014-05-15 (SIP, IE, PRMU, MI) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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Download PDF SIP2014-11 IE2014-11 PRMU2014-11 MI2014-11

Conference Information
Committee PRMU MI IE SIP  
Conference Date 2014-05-22 - 2014-05-23 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SIP 
Conference Code 2014-05-PRMU-MI-IE-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Signal Processing for Lung-Sound Recognition 
Sub Title (in English) Separation and Classification of Continuous and Discontinuous Adventitious Sounds 
Keyword(1) Respiratory system diagnosis  
Keyword(2) Electronic auscultation  
Keyword(3) Signal separation  
Keyword(4) Robust PCA  
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1st Author's Name Tomoya Sakai  
1st Author's Affiliation Nagasaki University (Nagasaki Univ.)
2nd Author's Name Takahiro Uchida  
2nd Author's Affiliation Nagasaki University (Nagasaki Univ.)
3rd Author's Name Aeri Sakaguchi  
3rd Author's Affiliation Nagasaki University (Nagasaki Univ.)
4th Author's Name Senya Kiyasu  
4th Author's Affiliation Nagasaki University (Nagasaki Univ.)
5th Author's Name Sueharu Miyahara  
5th Author's Affiliation formerly Nagasaki University (formerly Nagasaki Univ.)
6th Author's Name Mikio Oka  
6th Author's Affiliation Kawasaki Medical School (Kawasaki Med. Sch.)
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Speaker
Date Time 2014-05-22 16:20:00 
Presentation Time 30 
Registration for SIP 
Paper # IEICE-SIP2014-11,IEICE-IE2014-11,IEICE-PRMU2014-11,IEICE-MI2014-11 
Volume (vol) IEICE-114 
Number (no) no.39(SIP), no.40(IE), no.41(PRMU), no.42(MI) 
Page pp.55-60 
#Pages IEICE-6 
Date of Issue IEICE-SIP-2014-05-15,IEICE-IE-2014-05-15,IEICE-PRMU-2014-05-15,IEICE-MI-2014-05-15 


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