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Human upper limb movement trajectories have been shown to be quite smooth, in that time derivatives of end point position (r), including d 3r/dt 3 (i.e., jerk), appear to be minimized during rapid voluntary reaching tasks. Studies have suggested that these movements are implemented by an optimal neural controller which seeks to minimize a cost function, such as average jerk cost, over the course of these motions. While this hypothetical control strategy is widely supported, there are substantial difficulties associated with implementing such a controller, including ambiguities inherent in transformations from Cartesian to joint coordinates, and the lack of appropriate transducers to provide information about higher derivatives of limb motion to the nervous system. Given these limitations, the authors evaluate the possibility that smoothing of movement might be induced primarily by the intrinsic mechanical properties of muscle by recording the trajectories of inertially loaded muscle with the excitatory input held constant. These trajectories are compared with those predicted by a minimum-jerk optimization model, and by a Hill-based muscle model. The authors' results indicate that trajectories produced by inertially loaded muscle alone are smooth (in the minimum-jerk sense), and that muscle properties may suffice to account for much of the observed smoothing of voluntary motion, obviating the need for an optimizing neural strategy.