Total knee replacement (TKR) surgery decreases pain and increases functional mobility for patients with joint disease. As primary TKRs are implanted in patients who are younger, heavier, and more active (1), increases in wear and TKR revision rates are expected. Preclinical analysis of TKRs with mathematical models and experimental tests require accurate in vivo kinetic and kinematic input data. Kinematics can be obtained with gait analysis, but in vivo force data are just beginning to become available from instrumented TKRs from only a few patients (2). Patient gait is highly variable both within and between individuals and can be influenced by a variety of factors including the progression and history of joint disease, surgical procedure, and TKR design. Variation in patient gait and activities results in subsequent contact force and polyethylene wear variability. A validated mathematical model which calculates contact forces for alternate input data could add valuable insight for preclinical testing. A problem facing mathematical modeling is that there are too many unknowns to directly solve for contact forces. In order to approach this problem, we have developed a knee mathematical model that allows parametric variation of muscle activation levels (3) and calculates a solution space of physically possible contact forces.

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