Sounds, such as clicking and/or crepitation, evoked in the temporomandibula
r Claw) joint during function may indicate pathology, Analysis of the reduc
ed interference time-frequency distribution of these sounds is of diagnosti
c value. However, visual evaluation is expensive and error prone, and there
is, thus, a need for automated analysis. The aim of this study was to find
the optimal signal representation and pattern recognition method for compu
terized classification of temporomandibular joint sounds. Concepts of time-
shift invariance with and without scale invariance were employed and mutual
ly compared. The automated analysis methods provided classification results
that were similar to previous visual classification of the sounds, It was
found that the classifier performance was significantly improved when scale
invariance was omitted, This behavior occurred because scale invariance in
terfered with the frequency content of the signal. Therefore, scale invaria
nce should not be pursued in the classification scheme employed in this stu
dy.