How sensitive are predicted muscle and knee contact forces to normalization factors and polynomial order in the muscle recruitment criterion formulation?

Musculoskeletal modeling is an important tool to estimate knee loads. In these models, anatomical muscles are frequently sub-divided to account for wide origin/insertion areas. The specific sub-division has been shown to affect some muscle recruitment criteria and it has been suggested that normalization factors should be incorporated into models. The primary aim of this study was to investigate the effect of different muscle normalization factors in the muscle recruitment criterion and polynomial order on the estimated muscle and total, medial and lateral knee contact forces during gait. These were evaluated on three different musculoskeletal models with increasing levels of patient-specificity and knee joint model complexity for one subject from the Grand Challenge data set and evaluated against measured forces. The results showed that the introduction of the muscle normalization factors affected the estimated forces and that this effect was most pronounced when a polynomial of order two was applied. Additionally, mainly the second contact force peak was affected. Secondary investigations revealed that the predicted forces can vary substantially as a function of the knee flexor and extensor muscle strength with over one body weight difference in predicted total compressive force between 100% and 40% of the strength. Additionally, the predicted second peak during gait was found to be sensitive to the position of the pelvic skin marker positions in the model. These results imply that caution should be taken when a normalization factor is introduced to account for sub-divided muscles especially for second-order recruitment criteria

A forward dynamics methodology to study nonlinear dynamics and wear of total knee arthroplasties

The present study aims at developing a forward dynamics methodology to specify the micro- and macro-motion of the tibiofemoral joint where the ligament behavior is simulated by employing an asymmetric nonlinear elastic model. Point clouds associated with the knee components are smoothed using a Laplacian smoothing procedure. Two phases of the contact search, i.e., spatial contact search and contact detection, are in turn performed to determine nodes and elements in contact while a bounding box technique is implemented to reduce associated computational time. External loads and moment due to the presence of all soft tissues are acquired using a musculoskeletal approach and fed into the forward dynamic model. Archard wear law is also integrated into the model allowing for wear prediction of total knee arthroplasty (TKA). A mesh density analysis is performed and the developed approach is assessed against outcomes available in the literature. Trajectory and wear occurrence of TKA is obtained, and it is shown that friction can lead to changes in both of them