DocumentCode
2410440
Title
Multi-resolution decomposition applied to crackle detection
Author
Du, M. ; Lam, F.K. ; Chan, F.H.Y. ; Sun, J.
Author_Institution
Dept. of Electr. & Electron. Eng., Hong Kong Univ., Hong Kong
Volume
5
fYear
1997
fDate
12-15 Oct 1997
Firstpage
4223
Abstract
Crackles, heard over the lungs in a variety of diseases, are one of the most important physical signs in clinical medicine. They have an explosive pattern in the time domain, with a rapid onset and short duration. The timing, repeatability and shape of crackles are important parameters for diagnosis. Therefore, automatic detection of crackles and their classification as fine and coarse crackles have important clinical value. Since the multi-resolution decomposition technique can give high resolution in both time and frequency, it can be exploited to detect crackles and to classify them according to the information in each scale. In this paper, we present a new method for crackle detection based on the continuous wavelet transform. The theory, methods and experimental results are given in detail in this paper
Keywords
acoustic signal processing; bioacoustics; lung; medical signal processing; patient diagnosis; pattern classification; pneumodynamics; time-domain analysis; wavelet transforms; automatic crackle detection; clinical medicine; continuous wavelet transform; crackle classification; crackle shape; diseases; explosive pattern; lung sound; medical diagnosis; multi-resolution decomposition technique; repeatability; timing; Continuous wavelet transforms; Diseases; Energy resolution; Explosives; Frequency; Lungs; Multiresolution analysis; Shape; Timing; Wavelet transforms;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location
Orlando, FL
ISSN
1062-922X
Print_ISBN
0-7803-4053-1
Type
conf
DOI
10.1109/ICSMC.1997.637362
Filename
637362
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