Several opensource or commercially available software platforms are widely used to develop dynamic simulations of movement. While computational approaches are conceptually similar across platforms, technical differences in implementation may influence output. We present a new upper limb dynamic model as a tool to evaluate potential differences in predictive behavior between platforms. We evaluated to what extent differences in technical implementations in popular simulation software environments result in differences in kinematic predictions for single and multijoint movements using EMG- and optimization-based approaches for deriving control signals. We illustrate the benchmarking comparison using SIMM-Dynamics Pipeline-SD/Fast and OpenSim platforms. The most substantial divergence results from differences in muscle model and actuator paths. This model is a valuable resource and is available for download by other researchers. The model, data, and simulation results presented here can be used by future researchers to benchmark other software platforms and software upgrades for these two platforms.

This study utilizes a biomechanical model of the thumb to estimate the force produced at the thumb-tip by each of the four extrinsic muscles. We used the principle of virtual work to relate joint torques produced by a given muscle force to the resulting endpoint force and compared the results to two separate cadaveric studies. When we calculated thumb-tip forces using the muscle forces and thumb postures described in the experimental studies, we observed large errors. When relatively small deviations from experimentally reported thumb joint angles were allowed, errors in force direction decreased substantially. For example, when thumb posture was constrained to fall within ±15° of reported joint angles, simulated force directions fell within experimental variability in the proximal-palmar plane for all four muscles. Increasing the solution space from ±1° to an unbounded space produced a sigmoidal decrease in error in force direction. Changes in thumb posture remained consistent with a lateral pinch posture, and were generally consistent with each muscle’s function. Altering thumb posture alters both the components of the Jacobian and muscle moment arms in a nonlinear fashion, yielding a nonlinear change in thumb-tip force relative to muscle force. These results explain experimental data that suggest endpoint force is a nonlinear function of muscle force for the thumb, support the continued use of methods that implement linear transformations between muscle force and thumb-tip force for a specific posture, and suggest the feasibility of accurate prediction of lateral pinch force in situations where joint angles can be measured accurately.

The human body continues to be an inspiration for the work of a myriad of different fields, both scientific and mathematic. In particular, robotics draws upon the motions and relationships of different human systems in order to reproduce similar mobility while performing different tasks. The human shoulder–arm–elbow complex has been one of the most difficult to exactly replicate. This paper examines the relationship between the motion of the shoulder while positioning the center of the wrist during voluntary arm movements and the resulting orientation of the arm, in particular the direction of the axis passing through the elbow joint. Experimental data is presented that was used to quantify this coupling between the reaching direction of the arm and the elbow axis direction. The results from this paper are two surface‐fit equations that can be used to determine the elbow axis direction when given the location of the wrist center. These results are useful when considering the design and control of shoulder–arm–elbow complex models.

There are several opensource or commercially available software platforms widely used for the development of dynamic simulations of movement. While computational approaches to calculating the dynamics of a musculoskeletal model are conceptually similar across platforms, differences in implementation may influence simulation output. To understand predictions made using simulation, it is important to understand differences that may result from the choice of model or platform. Our aims were to 1) develop a musculoskeletal model of the upper limb suitable for dynamic simulation and 2) evaluate the influence of the choice between SIMM-SD/Fast and OpenSim simulation platforms on gravity- and EMG-driven simulations of movement.