咀嚼運動における平均経路予測モデルの開発

概要

論文の詳細を見る
The purpose of this study was to develop a new statistical model to predict mandibular kinematics, especially for chewing cycles. Two subjects without indicators or symptoms of temporomandibular disorders and with normal occlusion and anterior crossbite were selected. The chewing movement of the mouth was recorded by an opto-electric system (TRIMET system). Each curve was modeled as spline function with random coefficients. To determine the optimal number of knots, two criteria were used : DIC (deviance information criteria) and pD (effective number of parameters). The aim was to estimate a typical population curve. Self-modeling regression (SEMOR) was extended to three dimensions to model groups of three-dimensional curves. Each curve was modeled as a spline function using 25 knots, and a population average curve was created using SEMOR. The chewing cycles were modeled using a combination of spline function with random coefficients and SEMOR. These models provide a new tool for the analysis of mandibular kinematics to understand commonalities and difference among subjects.