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Melzer, I., Liebermann, D. G., Krasovsky, T., & Oddsson, L. I. E. (2010). Cognitive load affects lower limb force-time relations during voluntary rapid stepping in healthy old and young adults. J Gerontol A Biol Sci Med Sci, 65(4), 400–406.
Abstract: BACKGROUND: Quick step execution may prevent falls when balance is lost; adding a concurrent task delays this function. We investigate whether push-off force-time relations during the execution of rapid voluntary stepping is affected by a secondary task in older and young adults. METHODS: Nineteen healthy older adults and 12 young adults performed rapid voluntary stepping under single- and dual-task conditions. Peak power, peak force, and time to peak force during preparatory and swing phases of stepping were extracted from center of pressure and ground reaction force data. RESULTS: For dual-task condition compared with single-task condition, older adults show a longer time to reach peak force during the preparation and swing phases compared with young adults (approximately 25% vs approximately 10%, respectively). Peak power and peak force were not affected by a concurrent attention-demanding task. CONCLUSION: Older adults have difficulty allocating sufficient attention for fast muscle recruitment when concurrently challenged by an attention-demanding task.
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Friedman, J., & Flash, T. (2007). Task-dependent selection of grasp kinematics and stiffness in human object manipulation. Cortex, 43(3), 444–460.
Abstract: Object manipulation with the hand is a complex task. The task has redundancies at many levels, allowing many possibilities for the selection of grasp points, the orientation and posture of the hand, the forces to be applied at each fingertip and the impedance properties of the hand. Despite this inherent complexity, humans perform object manipulation nearly effortlessly. This article presents experimental findings of how humans grasp and manipulate objects, and examines the compatibility of grasps selected for specific tasks. This is accomplished by looking at the velocity transmission and force transmission ellipsoids, which represent the transmission ratios of the corresponding quantity from the joints to the object, as well as the stiffness ellipsoid which represents the directional stiffness of the grasp. These ellipsoids allow visualization of the grasp Jacobian and grasp stiffness matrices. The results show that the orientation of the ellipsoids can be related to salient task requirements.
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Friedman, J., Latash, M. L., & Zatsiorsky, V. M. (2011). Directional variability of the isometric force vector produced by the hand in multi-joint planar tasks. Journal of Motor Behavior, 43(6), 451–463.
Abstract: Numerous studies have examined control of force magnitude, but relatively little research has considered force direction control. In this study, subjects applied isometric forces to a handle and we compared within-trial variability when producing force in different directions. The standard deviation (SD) of the force parallel to the prescribed direction of force production increased linearly with the targeted force level, as did the SD of the force perpendicular to the instructed direction. In contrast, the SD of the angle of force production decreased with increased force level. In the four (of eight) instructed force directions where the endpoint force was generated due to a joint torque in only one joint (either the shoulder or elbow) the principal component axes in force space were well aligned with the prescribed direction of force production. In the other directions, the variance was approximately equal along the two force axes. The variance explained by the first principal component was significantly larger in torque space compared to the force space, and mostly corresponded to positive correlation between the joint torques. Such coordinated changes suggest that the torque variability was mainly due to the variability of the common drive to the muscles serving two joints, although this statement needs to be supported by direct studies of muscle activation in the future.
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Friedman, J., & Flash, T. (2009). Trajectory of the index finger during grasping. Exp Brain Res, 196(4), 497–509.
Abstract: The trajectory of the index finger during grasping movements was compared to the trajectories predicted by three optimization-based models. The three models consisted of minimizing the integral of the weighted squared joint derivatives along the path (inertia-like cost), minimizing torque change, and minimizing angular jerk. Of the three models, it was observed that the path of the fingertip and the joint trajectories, were best described by the minimum angular jerk model. This model, which does not take into account the dynamics of the finger, performed equally well when the inertia of the finger was altered by adding a 20 g weight to the medial phalange. Thus, for the finger, it appears that trajectories are planned based primarily on kinematic considerations at a joint level.
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Liebermann, D. G., Krasovsky, T., & Berman, S. (2008). Planning maximally smooth hand movements constrained to nonplanar workspaces. J Mot Behav, 40(6), 516–531.
Abstract: The article characterizes hand paths and speed profiles for movements performed in a nonplanar, 2-dimensional workspace (a hemisphere of constant curvature). The authors assessed endpoint kinematics (i.e., paths and speeds) under the minimum-jerk model assumptions and calculated minimal amplitude paths (geodesics) and the corresponding speed profiles. The authors also calculated hand speeds using the 2/3 power law. They then compared modeled results with the empirical observations. In all, 10 participants moved their hands forward and backward from a common starting position toward 3 targets located within a hemispheric workspace of small or large curvature. Comparisons of modeled observed differences using 2-way RM-ANOVAs showed that movement direction had no clear influence on hand kinetics (p < .05). Workspace curvature affected the hand paths, which seldom followed geodesic lines. Constraining the paths to different curvatures did not affect the hand speed profiles. Minimum-jerk speed profiles closely matched the observations and were superior to those predicted by 2/3 power law (p < .001). The authors conclude that speed and path cannot be unambiguously linked under the minimum-jerk assumption when individuals move the hand in a nonplanar 2-dimensional workspace. In such a case, the hands do not follow geodesic paths, but they preserve the speed profile, regardless of the geometric features of the workspace.
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