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Neuromuscular control of complex, multi-segment movements is often investigated with a modeling and computer simulation approach. Because a given movement can be completed using many different coordination choices, an optimization framework is often used to determine the muscle activity patterns that best accomplish the movement task. This framework is well suited to simulating movements whose performance objectives are easily specified by mathematical functions, such as vertical jumping for maximum height. However, these motion simulations tend to be difficult optimization problems because they contain many local optima that add complexity to the solution domain of the objective function 1–3.
Miller et al. (2008) studied this question.