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Conference Paper: Multi-resolution decomposition applied to crackle detection

TitleMulti-resolution decomposition applied to crackle detection
Authors
KeywordsComputers
Cybernetics
Issue Date1997
PublisherIEEE.
Citation
Computational Cybernetics and Simulation, IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings, Orlando, Florida, USA, 12-15 October 1997, v. 5, p. 4223-4226 How to Cite?
AbstractCrackles, 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.
Persistent Identifierhttp://hdl.handle.net/10722/46043
ISSN

 

DC FieldValueLanguage
dc.contributor.authorDu, Men_HK
dc.contributor.authorLam, FKen_HK
dc.contributor.authorChan, FHYen_HK
dc.contributor.authorSun, Jen_HK
dc.date.accessioned2007-10-30T06:41:18Z-
dc.date.available2007-10-30T06:41:18Z-
dc.date.issued1997en_HK
dc.identifier.citationComputational Cybernetics and Simulation, IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings, Orlando, Florida, USA, 12-15 October 1997, v. 5, p. 4223-4226en_HK
dc.identifier.issn1062-922Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46043-
dc.description.abstractCrackles, 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.en_HK
dc.format.extent299851 bytes-
dc.format.extent13817 bytes-
dc.format.extent8841 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©1997 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectComputersen_HK
dc.subjectCyberneticsen_HK
dc.titleMulti-resolution decomposition applied to crackle detectionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1062-922X&volume=5&spage=4223&epage=4226&date=1997&atitle=Multi-resolution+decomposition+applied+to+crackle+detectionen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ICSMC.1997.637362en_HK
dc.identifier.hkuros34618-

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