Is the effect of a countermovement on jump height due to active state development?

Purpose: To investigate whether the difference in jump height between countermovement jumps (CMJ) and squat jumps (SJ) could be explained by a difference in active state during propulsion. Methods: Simulations were performed with a model of the human musculoskeletal system comprising four body segments and six muscles. The model's only input was STIM, the stimulation of muscles, which could be switched "off" or "on." After switching "on," STIM increased to its maximum at a fixed rate of change (dSTIM/dt). For various values of dSTIM/dt, stimulation switch times were optimized to produce a maximum height CMJ. From this CMJ, the configuration at the lowest height of the center of gravity (CG) was selected and used as static starting configuration for simulation of SJ. Next, STIM-switch times were optimized to find the maximum height SJ. Results: Simulated CMJ and SJ closely resembled jumps of human subjects. Maximum jump height of the model was greater in CMJ than in SJ, with the difference ranging from 0.4 cm at infinitely high dSTIM/dt to about 2.5 cm at the lowest dSTIM/dt investigated. The greater jump height in CMJ was due to a greater work output of the hip extensor muscles. These muscles could produce more force and work over the first 30% of their shortening range in CMJ, due to the fact that they had a higher active state in CMJ than in SJ. Conclusion: 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. Copyright © 2005 by the American College of Sports Medicine

Humans adjust control to initial squat depth in vertical squat jumping

The purpose of this study was to gain insight into the control strategy that humans use in jumping. Eight male gymnasts performed vertical squat jumps from five initial postures that differed in squat depth (P1-P5) while kinematic data, ground reaction forces, and electromyograms (EMGs) of leg muscles were collected; the latter were rectified and smoothed to obtain SREMGs. P3 was the preferred initial posture; in P1, P2, P4, and P5 height of the mass center was +13, +7, -7 and -14 cm, respectively, relative to that in P3. Furthermore, maximum-height jumps from the initial postures observed in the subjects were simulated with a model comprising four body segments and six Hill-type muscles. The only input was the onset of stimulation of each of the muscles (Stim). The subjects were able to perform well-coordinated squat jumps from all postures. Peak SREMG levels did not vary among P1-P5, but SREMG onset of plantarflexors occurred before that of gluteus maximus in P1 and >90 ms after that in P5 (P < 0.05). In the simulation study, similar systematic shifts occurred in Stim onsets across the optimal control solutions for jumps from P1-P5. Because the adjustments in SREMG onsets to initial posture observed in the subjects were very similar to the adjustments in optimal Stim onsets of the model, it was concluded that the SREMG adjustments were functional, in the sense that they contributed to achieving the greatest jump height possible from each initial posture. For the model, we were able to develop a mapping from initial posture to Stim onsets that generated successful jumps from P1-P5. It appears that to explain how subjects adjust their control to initial posture there is no need to assume that the brain contains an internal dynamics model of the musculoskeletal system. Copyright © 2008 the American Physiological Society

Explanation of the bilateral deficit in human vertical squat jumping

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, ∼75% of thebilateral 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. Copyright © 2006 the American Physiological Society

Factors underlying the perturbation resistance of the trunk in the first part of a lifting movement

In the first part of lifting movements, the trunk movement is surprisingly resistant to perturbations. This study examined which factors contribute to this perturbation resistance of the trunk during lifting. Three possible mechanisms were studied: force-length-velocity characteristics of muscles, the momentum of the trunk as well as the effect of passive extending of the elbows. A forward dynamics modelling and simulation approach was adopted with two different input signals: (1) stimulation of Hill-type muscles versus (2) net joint moments. Experimental data collected during an unperturbed lifting movement were used as a reference, which a simulated lifting movement had to resemble. Subsequently, the simulated lifting movement was perturbed by applying 10 kg extra mass at the wrist (both before and after lift-off and with/without a fixed elbow), without modifying the input signals. The momentum of the trunk appeared to be insufficient to explain the perturbation resistance of trunk movements as found experimentally. In addition to the momentum of the trunk, the force-length-velocity characteristics of the muscles are necessary to account for the observed perturbation resistance. Initial extension of the elbow due to the mass perturbation delayed the propagation of the load to the shoulder. However, this delay is reduced due to the impedance at the elbow provided by the characteristics of muscles spanning the elbow. So, the force-length-velocity characteristics of the muscles spanning the elbow joint increase the perturbation at the trunk. © Springer-Verlag 2005

The merits of a parallel genetic algorithm in solving hard optimization problems

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

Humans make near-optimal adjustments of control to initial body configuration in vertical squat jumping

We investigated adjustments of control to initial posture in squat jumping. Eleven male subjects jumped from three initial postures: preferred initial posture (PP), a posture in which the trunk was rotated 18° more backward (BP) and a posture in which it was rotated 15° more forward (FP) than in PP. Kinematics, ground reaction forces and electromyograms (EMG) were collected. EMG was rectified and smoothed to obtain smoothed rectified EMG (srEMG). Subjects showed adjustments in srEMG histories, most conspicuously a shift in srEMG-onset of rectus femoris (REC): from early in BP to late in FP. Jumps from the subjects' initial postures were simulated with a musculoskeletal model comprising four segments and six Hill-type muscles, which had muscle stimulation (STIM) over time as input. STIM of each muscle changed from initial to maximal at STIM-onset, and STIM-onsets were optimized using jump height as criterion. Optimal simulated jumps from BP, PP and FP were similar to jumps of the subjects. Optimal solutions primarily differed in STIM-onset of REC: from early in BP to late in FP. Because the subjects' adjustments in srEMG-onsets were similar to adjustments of the model's optimal STIM-onsets, it was concluded that the former were near-optimal. With the model we also showed that near-maximum jumps from BP, PP and FP could be achieved when STIM-onset of REC depended on initial hip joint angle and STIM-onsets of the other muscles were posture-independent. A control theory that relies on a mapping from initial posture to STIM-onsets seems a parsimonious alternative to theories relying on internal optimal control models. © 2013 IBRO