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Knowledge of muscle forces and joint reaction forces during human movement can provide insight into the underlying control and tissue loading. Since direct measurement of the internal loads is generally not feasible, non-invasive methods based on musculoskeletal modeling and computer simulations have been extensively developed. By applying observed motion data to the musculoskeletal models, inverse dynamic analysis allow to determine the resultant joint torques, transformed then into estimates of individual muscle forces by means of different optimization procedures. Assessment of the joint reaction forces and other internal loads is further possible. Comparison of the muscle force estimates obtained for different modeling assumptions and parameters in the model can be valuable for the improvement of validity of the model-based estimations. The present study is another contribution to this field. Using a sagittal plane model of an upper limb with a weight carried in hand, and applying the data of recorded flexion and extension movement of the upper limb, the resultant muscular forces are predicted using different modeling assumptions and simulation tools. This study relates to different coordinates (joint and natural coordinates) used to built the mathematical model, muscle path modeling, muscle decomposition (change in number of the modeled muscles), and different optimization methods used to share the joint torques into individual muscles.

Influence of selected modeling and computational issues on muscle force estimates