Computational models often represent the most cost-effective approach to predict the behavior of musculoskeletal systems. Historically, dynamic musculoskeletal simulations have simplified representations of soft tissue structures, which makes it impossible to investigate the relationship between neuromuscular control and tissue loading. It is possible to overcome this limiting assumption by coupling a finite element model, e.g. of a foot, directly with a musculoskeletal model, e.g. of the lower extremity [1]. The goal of the current study was to apply this concept to the control of human gait and demonstrate that it is possible to have a gait pattern that minimizes internal foot deformation while satisfying an overall movement goal, e.g. minimal deviations from normal gait. Successful implementation will have wide-ranging implications such as finding therapeutic and rehabilitative movement patterns that relieve localized tissue loading.
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