It has been shown in previous research that the initial phase of EMG for a punching movement remained almost unchanged regardless of whether an external force was applied to the arm. The purpose of the present study was to explain this finding with the help of simulations. A two-dimensional model of me arm actuated by 6 Hill-type muscles was used to simulate a punching movement in the horizontal plane from a prescribed starting position with 90° elbow flexion. Input to the model was the stimulation of me muscles, and output were, among others, muscle forces and segmental accelerations. A genetic algorithm was used to determine the muscle onset times mat minimized movement duration and targeting error. In a subsequent forward simulation, the optimized muscle onset times for an unloaded punching movement were superimposed on the isometric stimulation necessary to hold me arm in the starting position while an external force was applied to the arm. The resulting movement was only slightly different from the unloaded movement. It appeared that because of the low level of isometric muscle force prior to the movement, and the high level of stimulation during the movement, muscle force was increased at a rate mat was almost independent of the prior force level. These results confirmed the suggestion that the initial phase of EMG in ballistic movements is more related to the rate of change of force than to the absolute force level. It is hypothesized mat this may simplify the task of the nervous system in the choice of initial muscle activity in ballistic arm movements because no adjustments to varying external forces are required.
Tom G. Welter and Maarten F. Bobbert
L.J. Richard Casius, Maarten F. Bobbert, and Arthur J. van Soest
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.