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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. (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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Raveh, E., Friedman, J., & Portnoy, S. (2018). Visuomotor behaviors and performance in a dual-task paradigm with and without vibrotactile feedback when using a myoelectric controlled hand. Assistive Technology, 30, 274–280.
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Friedman, J., SKM, V., Zatsiorsky, V. M., & Latash, M. L. (2009). The sources of two components of variance: an example of multifinger cyclic force production tasks at different frequencies. Exp Brain Res, 196(2), 263–277.
Abstract: In a multifinger cyclic force production task, the finger force variance measured across trials can be decomposed into two components, one that affects the combined force output (“bad variance”) and one that does not (“good variance”). Previous studies have found similar time patterns of “bad variance” and force rate leading to an approximately linear relationship between them. Based on this finding and a recently developed model of multifinger force production, we expected the “bad variance” during cyclic force production to increase monotonically with the rate of force change, both within a cycle and across trials at different frequencies. Alternatively, “bad variance” could show a dependence on task frequency, not on actual force derivative values. Healthy subjects were required to produce cyclic force patterns to prescribed targets by pressing on unidimensional force sensors, at a frequency set by a metronome. The task was performed with only the index finger, and with all four fingers. In the task with all four fingers, the “good variance” increased approximately linearly with an increase in the force magnitude. The “bad variance” showed within-a-cycle modulation similar to that of the force rate. However, an increase in the frequency did not lead to an increase in the “bad variance” that could be expected based on the natural relationships between action frequency and the rate of force change modulation. The results have been interpreted in the framework of an earlier model of multifinger force production where “bad variance” is a result of variance of the timing parameter. The unexpected lack of modulation of the “bad variance” with frequency suggests a drop in variance of the timing parameter with increased frequency. This mechanism may serve to maintain a constant acceptable level of variance under different conditions.
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Latash, M. L., Friedman, J., Kim, S.W., Feldman, A.G., Zatsiorsky, V.M. (2010). Prehension Synergies and Control with Referent Hand Configurations. Exp Brain Res, 202(1), 213–229.
Abstract: We used the framework of the equilibrium-point hypothesis (in its updated form based on the notion of referent configuration) to investigate the multi-digit synergies at two levels of a hypothetical hierarchy involved in prehensile actions. Synergies were analyzed at the thumb-virtual finger level (virtual finger is an imaginary digit with the mechanical action equivalent to that of the four actual fingers) and at the individual finger level. The subjects performed very quick vertical movements of a handle into a target. A load could be attached off-center to provide a pronation or supination torque. In a few trials, the handle was unexpectedly fixed to the table and the digits slipped off the sensors. In such trials, the hand stopped at a higher vertical position and rotated into pronation or supination depending on the expected torque. The aperture showed non-monotonic changes with a large, fast decrease and further increase, ending up with a smaller distance between the thumb and the fingers as compared to unperturbed trials. Multi-digit synergies were quantified using indices of co-variation between digit forces and moments of force across unperturbed trials. Prior to the lifting action, high synergy indices were observed at the individual finger level while modest indices were observed at the thumb-virtual finger level. During the lifting action, the synergies at the individual finger level disappeared while the synergy indices became higher at the thumb-virtual finger level. The results support the basic premise that, within a given task, setting a referent configuration may be described with a few referent values of variables that influence the equilibrium state, to which the system is attracted. Moreover, the referent configuration hypothesis can help interpret the data related to the trade-off between synergies at different hierarchical levels.
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