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When human hoppers are surprised by a change in surface stiffness, they adapt almost instantly by changing leg stiffness, implying that neural feedback is not necessary. The goal of this simulation study was first to investigate whether leg stiffness can change without neural control adjustment when landing on an unexpected hard or unexpected compliant (soft) surface, and second to determine what underlying mechanisms are responsible for this change in leg stiffness. The muscle stimulation pattern of a forward dynamic musculoskeletal model was optimized to make the model match experimental hopping kinematics on hard and soft surfaces. Next, only surface stiffness was changed to determine how the mechanical interaction of the musculoskeletal model with the unexpected surface affected leg stiffness. It was found that leg stiffness adapted passively to both unexpected surfaces. On the unexpected hard surface, leg stiffness was lower than on the soft surface, resulting in close-to-normal center of mass displacement. This reduction in leg stiffness was a result of reduced joint stiffness caused by lower effective muscle stiffness. Faster flexion of the joints due to the interaction with the hard surface led to larger changes in muscle length, while the prescribed increase in active state and resulting muscle force remained nearly constant in time. Opposite effects were found on the unexpected soft surface, demonstrating the bidirectional stabilizing properties of passive dynamics. These passive adaptations to unexpected surfaces may be critical when negotiating disturbances during locomotion across variable terrain.

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.