Abstract:Analysis of knee joint vibration (VAG) signals can provide quantitative indices for detection of knee joint pathology at an early stage. In addition to the statistical features developed in the related previous studies, we extracted two separable features, that is, the number of atoms derived from the wavelet matching pursuit decomposition and the number of significant signal turns
detected with the fixed threshold in the time domain. To perform a better classification over the data set of 89 VAG signals, we a…
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