The greater jump height in CMJ than in SJ could be explained by the fact that in CMJ active state developed during the preparatory countermovement, whereas in SJ it inevitably developed during the propulsion phase, so that the muscles could produce more force and work during shortening in CMJ.

In the literature, it has been reported that the mechanical output per leg is less in two-leg jumps than in one-leg jumps. This so-called bilateral deficit has been attributed to a reduced neural drive to muscles in two-leg jumps. The purpose of the present study was to investigate the possible contribution of nonneural factors to the bilateral deficit in jumping. We collected kinematics, ground reaction forces, and electromyograms of eight human subjects performing two-leg and one-leg (right leg) squat jumps and calculated mechanical output per leg. We also used a model of the human musculoskeletal system to simulate two-leg and one-leg jumps, starting from the initial position observed in the subjects. The model had muscle stimulation as input, which was optimized using jump height as performance criterion. The model did not incorporate a reduced maximal neural drive in the two-leg jump. Both in the subjects and in the model, the work of the right leg was more than 20% less in the two-leg jump than in the one-leg jump. Peak electromyogram levels in the two-leg jump were reduced on average by 5%, but the reduction was only statistically significant in m. rectus femoris. In the model, approximately 75% of the bilateral deficit in work per leg was explained by higher shortening velocities in the two-leg jump, and the remainder was explained by lower active state of muscles. It was concluded that the bilateral deficit in jumping is primarily caused by the force-velocity relationship rather than by a reduction of neural drive.

From the results pertaining to the standard model, it is concluded that the optimal pedaling rate is not uniquely specified by the power-velocity relationship of muscle, as suggested in literature. From the results pertaining to the model lacking activation dynamics, it follows that activation dynamics plays a surprisingly large role in determining the optimal pedaling rate. It is concluded that the pedaling rate that maximizes mechanical power output in sprint cycling follows from the interaction between activation dynamics and Hill's power-velocity relationship.

Bobbert MF, Casius LJ, Sijpkens IW, Jaspers RT. Humans adjust control to initial squat depth in vertical squat jumping.

A parallel genetic algorithm for optimization is outlined, and its performance on both mathematical and biomechanical optimization problems is compared to a sequential quadratic programming algorithm, a downhill simplex algorithm and a simulated annealing algorithm. When high-dimensional non-smooth or discontinuous problems with numerous local optima are considered, only the simulated annealing and the genetic algorithm, which are both characterized by a weak search heuristic, are successful in finding the optimal region in parameter space. The key advantage of the genetic algorithm is that it can easily be parallelized at negligible overhead.