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
Link To Document :
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