DocumentCode
3273991
Title
HHT based lung sound crackle detection and classification
Author
Li, Zhenzhen ; Du, Minghui
Author_Institution
Coll. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
fYear
2005
fDate
13-16 Dec. 2005
Firstpage
385
Lastpage
388
Abstract
Crackles are discontinuous adventitious lung sounds, characterized by waveforms with a rapid onset and short duration. Traditional approaches to detect and classify crackles are mainly from the morphological aspect, however, the sharp patterns of crackles in frequency domain were overlooked. In this paper we employ the innovative HHT method to detect and classify crackles. By detecting peaks in time-frequency distribution derived from HHT, segments are extracted, then, crackles can be identified and classified efficiently. Relevant theories, methods and experimental results are given in detail.
Keywords
Hilbert transforms; acoustic signal detection; acoustic signal processing; bioacoustics; lung; medical signal detection; medical signal processing; time-frequency analysis; Hilbert Huang transform; lung sound crackle detection; sound classification; time-frequency distribution; Acoustical engineering; Diseases; Educational institutions; Explosives; Frequency domain analysis; Lungs; Signal analysis; Spectral analysis; Time frequency analysis; Wavelet analysis; Detection and classification; Hilbert Huang Transform; Lung sound Crackles;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Signal Processing and Communication Systems, 2005. ISPACS 2005. Proceedings of 2005 International Symposium on
Print_ISBN
0-7803-9266-3
Type
conf
DOI
10.1109/ISPACS.2005.1595427
Filename
1595427
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