Mathematical modeling and computer simulation play an increasingly important role in the search for answers to questions that cannot be addressed experimentally. One of the biggest challenges in forward simulation of the movements of the musculoskeletal system is finding an optimal control strategy. It is not uncommon for this type of optimization problem that the segment dynamics need to be calculated millions of times. In addition, these calculations typically consume a large part of the CPU time during forward movement simulations. As numerous human movements are two-dimensional (2-D) to a reasonable approximation, it is extremely convenient to have a dedicated, computational efficient method for 2-D movements. In this paper we shall present such a method. The main goal is to show that a systematic approach can be adopted which allows for both automatic formulation and solution of the equations of kinematics and dynamics, and to provide some fundamental insight in the mechanical theory behind forward dynamics problems in general. To illustrate matters, we provide for download an example implementation of the main segment dynamics algorithm, as well as a complete implementation of a model of human sprint cycling.
L.J. Richard Casius, Maarten F. Bobbert and Arthur J. van Soest
Kenneth Meijer, Peter Bosch, Maarten F. Bobbert, Arthur J. van Soest and Peter A. Huijing
The influence of parameter values (i.e., fiber optimum lengths and moment arms) and simplification of the geometry of a Hill-type muscle model on the prediction of normalized maximal isometric knee extension moment to knee joint angle relationship was studied. For that purpose, the geometry of m. quadriceps femoris was modeled in considerable detail, and all parameter values were determined on one set of cadaver specimens that had been selected for muscular appearance. The predicted relationship was compared to that measured in human subjects over the full range of physiological knee angles, and a good correspondence was found (r = .96). The good correspondence could be attributed to the substitution of realistic parameter values into the model. Incorporating complex muscle geometry into the model resulted in a small additional improvement of the prediction. It was speculated that the variation in results of cadaver measurements among studies reflects true differences caused by individuals' levels of physical activity in the period preceding death.