Fractal analysis of knee-joint vibroarthrographic signals

Diagnostic measures related to the deterioration of the articular cartilage surfaces of knee joints due to arthritis and other abnormalities may be derived from vibroarthrographic (VAG) signals. In the present work, we explore fractal analysis to parameterize the temporal and spectral variability of normal and abnormal VAG signals. The power spectrum analysis method was used with the 1/f model to derive estimates of the fractal dimension. Classification accuracy of up to A_z = 0.74 was obtained, in terms of the area under the receiver operating characteristics curve, with a database of 89 VAG signals. The result compares well with the performance of other features derived in previous related works and could help in the detection and monitoring of knee-joint pathology.