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A strategy of motor learning using adjustable parameters for arm movement

This paper presents a strategy of motor learning that acquires an internal model of the arm by using adjustable parameters for arm movement. This strategy gradually adjusts the parameters, such as the speed of an arm movement and the viscoelastic property values of the arm in the learning process. Learning control based on such a strategy eliminates a few weak points in many types of learning control models which have been proposed in the last decade. We will ascertain the efficiency of the proposed strategy by computer simulation using a mathematical model of the human arm.