Explosive movements such as throwing, kicking, and jumping are characterized by high velocity and short movement time. Due to the fact that latencies of neural feedback loops are long in comparison to movement times, correction of deviations cannot be achieved on the basis of neural feedback. In other words, the control signals must be largely preprogrammed. Furthermore, in many explosive movements the skeletal system is mechanically analogous to an inverted pendulum; in such a system, disturbances tend to be amplified as time proceeds. It is difficult to understand how an inverted-pendulum-like system can be controlled on the basis of some form of open loop control (albeit during a finite period of time only). To investigate if actuator properties, specifically the force-length-velocity relationship of muscle, reduce the control problem associated with explosive movement tasks such as human vertical jumping, a direct dynamics modeling and simulation approach was adopted. In order to identify the role of muscle properties, two types of open loop control signals were applied: STIM(t), representing the stimulation of muscles, and MOM(t), representing net joint movements. In case of STIM control, muscle properties influence the joint moments exerted on the skeleton; in case of MOM control, these moments are directly prescribed. By applying perturbations and comparing the deviations from a reference movement for both types of control, the reduction of the effect of disturbances due to muscle properties was calculated. It was found that the system is very sensitive to perturbations in case of MOM control; the sensitivity to perturbations is markedly less in case of STIM control. It was concluded that muscle properties constitute a peripheral feedback system that has the advantage of zero time delay. This feedback system reduces the effect of perturbations during human vertical jumping to such a degree that when perturbations are not too large, the task may be performed successfully without any adaptation of the muscle stimulation pattern.

Pinter IJ, van Swigchem R, van Soest AJ, Rozendaal LA. The dynamics of postural sway cannot be captured using a one-segment inverted pendulum model: a PCA on segment rotations during unperturbed stance. J Neurophysiol 100: 3197-3208, 2008. First published October 1, 2008 doi:10.1152/jn.01312.2007. Research on unperturbed stance is largely based on a one-segment inverted pendulum model. Recently, an increasing number of studies report a contribution of other major joints to postural control. Therefore this study evaluates whether the conclusions originating from the research based on a one-segment model adequately capture postural sway during unperturbed stance. High-pass filtered kinematic data (cutoff frequency 1/30 Hz) obtained over 3 min of unperturbed stance were analyzed in different ways. Variance of joint angles was analyzed. Principalcomponent analysis (PCA) was performed on the variance of lower leg, upper leg, and head-arms-trunk (HAT) angles, as well as on lower leg and COM angle (the orientation of the line from ankle joint to center of mass). It was found that the variance in knee and hip joint angles did not differ from the variance found in the ankle angle. The first PCA component indicated that, generally, the upper leg and HAT segments move in the same direction as the lower leg with a somewhat larger amplitude. The first PCA component relating ankle angle variance and COM angle variance indicated that the ankle joint angle displacement gives a good estimate of the COM angle displacement. The second PCA component on the segment angles partly explains the apparent discrepancy between these findings because this component points to a countermovement of the HAT relative to the ankle joint angle. It is concluded that postural control during unperturbed stance should be analyzed in terms of a multiple inverted pendulum model.

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.

To cite this Article Hofmijster, Mathijs J. , Landman, Erik H. J. , Smith, Richard M. and Van Soest, A. J. Knoek(2007) 'Effect of stroke rate on the distribution of net mechanical power in rowing', Journal of Sports Sciences, 25: 4,[403][404][405][406][407][408][409][410][411] To link to this Article: DOI: 10.1080/02640410600718046 URL: http://dx.doi.org/10.1080/02640410600718046Full terms and conditions of use: http://www.informaworld.com/terms-and-conditions-of-access.pdf This article may be used for research, teaching and private study purposes. Any substantial or systematic reproduction, re-distribution, re-selling, loan or sub-licensing, systematic supply or distribution in any form to anyone is expressly forbidden.The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.Effect of stroke rate on the distribution of net mechanical power in rowing Abstract The aim of this study was to assess the effect of manipulating stroke rate on the distribution of mechanical power in rowing. Two causes of inefficient mechanical energy expenditure were identified in rowing. The ratio between power not lost at the blades and generated mechanical power ( P rower ) and the ratio between power not lost to velocity fluctuations and P rower were used to quantify efficiency (e propelling and e velocity respectively). Subsequently, the fraction of P rower that contributes to the average velocity ( _ x boat ) was calculated (e net ). For nine participants, stroke rate was manipulated between 20 and 36 strokes per minute to examine the effect on the power flow. The data were analysed using a repeated-measures analysis of variance. Results indicated that at higher stroke rates, P rower , _ x boat , e propelling , and e net increase, whereas e velocity decreases (P 5 0.0001). The decrease in e velocity can be explained by a larger impulse exchange between rower and boat. The increase in e propelling can be explained because the work at the blades decreases, which in turn can be explained by a change in blade kinematics. The increase in e net results because the increase in e propelling is higher than the decrease in e velocity . Our results show that the power equation is an adequate conceptual model with which to analyse rowing performance.

Kistemaker DA, Van Soest AJ, Wong JD, Kurtzer I, Gribble PL. Control of position and movement is simplified by combined muscle spindle and Golgi tendon organ feedback. J Neurophysiol 109: 1126-1139, 2013. First published October 24, 2012 doi:10.1152/jn.00751.2012.-Whereas muscle spindles play a prominent role in current theories of human motor control, Golgi tendon organs (GTO) and their associated tendons are often neglected. This is surprising since there is ample evidence that both tendons and GTOs contribute importantly to neuromusculoskeletal dynamics. Using detailed musculoskeletal models, we provide evidence that simple feedback using muscle spindles alone results in very poor control of joint position and movement since muscle spindles cannot sense changes in tendon length that occur with changes in muscle force. We propose that a combination of spindle and GTO afferents can provide an estimate of muscle-tendon complex length, which can be effectively used for low-level feedback during both postural and movement tasks. The feasibility of the proposed scheme was tested using detailed musculoskeletal models of the human arm. Responses to transient and static perturbations were simulated using a 1-degree-of-freedom (DOF) model of the arm and showed that the combined feedback enabled the system to respond faster, reach steady state faster, and achieve smaller static position errors. Finally, we incorporated the proposed scheme in an optimally controlled 2-DOF model of the arm for fast point-to-point shoulder and elbow movements. Simulations showed that the proposed feedback could be easily incorporated in the optimal control framework without complicating the computation of the optimal control solution, yet greatly enhancing the system's response to perturbations. The theoretical analyses in this study might furthermore provide insight about the strong physiological couplings found between muscle spindle and GTO afferents in the human nervous system. sensorimotor control; tendon compliance; optimal control; perturbations IN THIS ARTICLE, we provide evidence that simple low-level spinal feedback using muscle spindles alone results in very poor control of joint position and movement. In short, this is because muscle spindles cannot detect the changes in muscletendon complex (MTC) length that occur as a consequence of tendon stretch. We propose that afferent signals from Golgi tendon organs (GTOs) can be seen as a proxy for tendon length and that, in combination with muscle spindles, they can be effectively used for low-level feedback during both postural and movement tasks. Before describing in more detail the specific aims of this study, we first provide an overview of the current view on the role of muscle spindles and GTOs relevant to this article.In recent years several theories have been postulated about how the central nervous system (CNS) controls position and movement. These theories all share the common premise that to control movements, the CNS must have information about the current state of the mu...