Sparse representation of audio features for sputum detection from lung sounds

Tatsuya Yamashita, Satoshi Tamura, Kenji Hayashi, Yutaka Nishimoto, Satoru Hayamizu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A medical staff needs to check sputum accumulation in patient's respiratory tract by lung sounds auscultation at any time, and it is the big burden for the staff. This paper aims to develop a system which notifies appropriate timing for the tracheal suction for the medical staff by analyzing lung sounds of the patients. We present a novel framework about automatic sputum detection from lung sounds. We proposed the sparse representation of audio features to realize robust detection in real environment. We showed the effectiveness of our proposed method for three patients in an ICU of Gifu University Hospital, where the recorded lung sounds included electronic beeps, human voices, and other various noises.

Original languageEnglish
Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
Pages2005-2008
Number of pages4
Publication statusPublished - 2012
Externally publishedYes
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: 2012 Nov 112012 Nov 15

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference21st International Conference on Pattern Recognition, ICPR 2012
Country/TerritoryJapan
CityTsukuba
Period12/11/1112/11/15

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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