Contact pressure in the knee joint is a key element in the mechanisms of knee pain and osteoarthritis. Assessing the contact pressure in tibiofemoral joint is a challenging mechanical problem due to uncertainty in material properties. In this study, a sensitivity analysis of tibiofemoral peak contact pressure to the material properties of the soft tissue was carried out through fractional factorial and Box-Behnken designs. The cartilage was modeled as linear elastic material, and in addition to its elastic modulus, interaction effects of soft tissue material properties were added compared to previous research. The results indicated that elastic modulus of the cartilage is the most effective factor. Interaction effects of axial/radial modulus with elastic modulus of cartilage, circumferential and axial/radial moduli of meniscus were other influential factors. Furthermore this study showed how design of experiment methods can help designers to reduce the number of finite element analyses and to better interpret the results. 1. Introduction Knee joint contact pressure is of critical importance in the mechanisms of knee pain and osteoarthritis [1, 2]. Computational models and finite element analyses (FEA) have been utilized to study contact characteristics of normal and injured knees, as well as total knee replacements (TKR) [3–8]. The purpose of these studies was to determine peak contact pressure in order to predict either tissue degradation of the knee or wear of ultra-high molecular weight polyethylene (UHMWPE) in TKR. Some biomechanical factors, such as material properties and geometries of tissues [9, 10], and knee kinematic [11] can affect the contact behavior of the knee and consequently the design of TKR. Impacts of horn attachments stiffness and meniscal material properties on tibiofemoral contact pressure using “semiautomatic” optimization method were investigated by Haut Donahue et al. [9], who set tolerances on the variables to restore the contact pressure to within a specified error. The authors, however, performed more than 60 analyses to determine whether an individual factor is of importance. Meanwhile, interaction effects between different factors were not considered in their study. In order to better interpret the effects of variations in the material properties of soft tissue, a powerful statistical approach is required to design computational experiments. Design of experiments (DOE) is a formal mathematical method that helps to solve complicated problems and to save time and resources (cost) by reducing the number of required
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