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Critical Reviews™ in Biomedical Engineering

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ISSN Print: 0278-940X

ISSN Online: 1943-619X

SJR: 0.262 SNIP: 0.372 CiteScore™:: 2.2 H-Index: 56

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Computer-Aided Diagnosis of Knee-Joint Disorders via Vibroarthrographic Signal Analysis: A Review

Volume 38, Issue 2, 2010, pp. 201-224
DOI: 10.1615/CritRevBiomedEng.v38.i2.60
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ABSTRACT

The knee is the lower-extremity joint that supports nearly the entire weight of the human body. It is susceptible to osteoarthritis and other knee-joint disorders caused by degeneration or loss of articular cartilage. The detection of a knee-joint abnormality at an early stage is important, because it helps increase therapeutic options that may slow down the degenerative process. Imaging-based arthrographic modalities can provide anatomical images of the joint cartilage surfaces, but fail to demonstrate the functional integrity of the cartilage. Knee-joint auscultation, by means of recording the vibroarthrographic (VAG) signal during bending motion of a knee, could be used to develop a noninvasive diagnostic tool. Computer-aided analysis of VAG signals could provide quantitative indices for screening of degenerative conditions of the cartilage surface and staging of osteoarthritis. In addition, the diagnosis of knee-joint pathology by means of VAG signal analysis may reduce the number of semi-invasive diagnostic arthroscopic examinations. This article reviews studies related to VAG signal analysis, first summarizing the pilot studies that demonstrated the diagnostic potential of knee-joint auscultation for the detection of degenerative diseases, and then describing the details of recent progress in analysis of VAG signals using temporal analysis, frequency-domain analysis, time-frequency analysis, and statistical modeling. The decision-making methods used in the related studies are summarized, followed by a comparison of the diagnostic performance achieved by different pattern classifiers. The final section is a perspective on the future and further development of VAG signal analysis.

CITED BY
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