Med Biol Eng Comput - Development of a subject-specific model to predict the forces in the knee ligaments at high flexion angles.

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Resumo

Recent clinical evidence has suggested that tasks performed in kneeling or squatting postures place the knee at a higher risk for injury because loads across the knee might overload the ligaments. The objective of this study was to develop a subject-specific model of the knee that is kinematically driven to predict the forces in the major ligaments at high flexion angles. The geometry of the femur, tibia, and fibula and the load-elongation curves representing the structural properties of the ACL, PCL, LCL, and MCL served as inputs to the model, which represented each ligament as a nonlinear elastic spring. To drive the model, kinematic data was obtained while loads were applied to the same cadaveric knee at four flexion angles. The force in each ligament during the recorded kinematic data allowed an optimization procedure to determine the location of the ligament attachment sites on each bone and their reference lengths. The optimization procedure could successfully minimize the differences between the experimental and predicted forces only when the kinematics at 90?, 120?, and 140? of flexion were utilized. This finding suggests that the ligaments at the knee function differently at high-flexion angles compared to low flexion angles and separate models must be used to examine each range of motion. In the future, the novel experimental and computational methodology will be used to construct additional models and additional knee kinematics will be input to help elucidate mechanisms of injury during tasks performed in kneeling or squatting postures.

Resumo Limpo

recent clinic evid suggest task perform kneel squat postur place knee higher risk injuri load across knee might overload ligament object studi develop subjectspecif model knee kinemat driven predict forc major ligament high flexion angl geometri femur tibia fibula loadelong curv repres structur properti acl pcl lcl mcl serv input model repres ligament nonlinear elast spring drive model kinemat data obtain load appli cadaver knee four flexion angl forc ligament record kinemat data allow optim procedur determin locat ligament attach site bone refer length optim procedur success minim differ experiment predict forc kinemat flexion util find suggest ligament knee function differ highflexion angl compar low flexion angl separ model must use examin rang motion futur novel experiment comput methodolog will use construct addit model addit knee kinemat will input help elucid mechan injuri task perform kneel squat postur

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