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Medical & Biological Engineering & Computing

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01.03.2008 | Original Article

Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions

verfasst von: Rangaraj M. Rangayyan, Y. F. Wu

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 3/2008

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Abstract

Externally detected vibroarthrographic (VAG) signals bear diagnostic information related to the roughness, softening, breakdown, or the state of lubrication of the articular cartilage surfaces of the knee joint. Analysis of VAG signals could provide quantitative indices for noninvasive diagnosis of articular cartilage breakdown and staging of osteoarthritis. We propose the use of statistical parameters of VAG signals, including the form factor involving the variance of the signal and its derivatives, skewness, kurtosis, and entropy, to classify VAG signals as normal or abnormal. With a database of 89 VAG signals, screening efficiency of up to 0.82 was achieved, in terms of the area under the receiver operating characteristics curve, using a neural network classifier based on radial basis functions.

Vorheriger Artikel Stability of the human upright stance depending on the frequency of external disturbances

Nächster Artikel Fully automated computer algorithm for calculating articular contact points with application to knee biomechanics

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Titel: Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions
verfasst von: Rangaraj M. Rangayyan
Y. F. Wu
Publikationsdatum: 01.03.2008
Verlag: Springer-Verlag
Erschienen in: Medical & Biological Engineering & Computing / Ausgabe 3/2008
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI: https://doi.org/10.1007/s11517-007-0278-7

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