Abstract

new method for detection of temporomandibulardisorder based on singular spectrum analysis is presented. In this method the motion data of markers placed on the points of special interest on the faces of several subjects is extracted and analysed. The individuals are classified into a group of healthy subjects and a group of those with temporomandibulardisorder by extracting the signal components of the original time series and separating the noise using the proposed technique. The results for both simulated and real data verify the effectiveness of the proposed algorithm.