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      A New Power Law Linking the Speed to the Geometry of Tool-Tip Orientation in Teleoperation of a Robot-Assisted Surgical System

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          Mathematics. Critical truths about power laws.

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            Science and Statistics

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              The coordination of arm movements: an experimentally confirmed mathematical model.

              This paper presents studies of the coordination of voluntary human arm movements. A mathematical model is formulated which is shown to predict both the qualitative features and the quantitative details observed experimentally in planar, multijoint arm movements. Coordination is modeled mathematically by defining an objective function, a measure of performance for any possible movement. The unique trajectory which yields the best performance is determined using dynamic optimization theory. In the work presented here, the objective function is the square of the magnitude of jerk (rate of change of acceleration) of the hand integrated over the entire movement. This is equivalent to assuming that a major goal of motor coordination is the production of the smoothest possible movement of the hand. Experimental observations of human subjects performing voluntary unconstrained movements in a horizontal plane are presented. They confirm the following predictions of the mathematical model: unconstrained point-to-point motions are approximately straight with bell-shaped tangential velocity profiles; curved motions (through an intermediate point or around an obstacle) have portions of low curvature joined by portions of high curvature; at points of high curvature, the tangential velocity is reduced; the durations of the low-curvature portions are approximately equal. The theoretical analysis is based solely on the kinematics of movement independent of the dynamics of the musculoskeletal system and is successful only when formulated in terms of the motion of the hand in extracorporal space. The implications with respect to movement organization are discussed.
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                Author and article information

                Contributors
                Journal
                IEEE Robotics and Automation Letters
                IEEE Robot. Autom. Lett.
                Institute of Electrical and Electronics Engineers (IEEE)
                2377-3766
                2377-3774
                October 2022
                October 2022
                : 7
                : 4
                : 10762-10769
                Affiliations
                [1 ]Department of Biomedical Engineering and the Zlotowsky Center for Neuroscience, Ben-Gurion University of the Negev, Beer Sheva, Israel
                [2 ]Department of Engineering, University of Cambridge, Cambridge, U.K.
                [3 ]Department of Orthopedic Surgery, Soroka Medical Center, Ben-Gurion University of the Negev, Beer Sheva, Israel
                Article
                10.1109/LRA.2022.3193485
                086cf2b7-fbac-45d2-a047-31572aa686cc
                © 2022

                https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-037

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