The method of kinematic analysis was sensitive for an assessment of motor recovery induced by CIMT. The kinematic results suggest that the increase in the use of the paretic limb in activities of daily living after the intervention is not only attributable to the patient's increased attention to it and better hand dexterity, but it is also a consequence of the improved speed of movement and better coordination between shoulder and elbow joints.

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This paper presents a robust and direct algorithm for the least-square fitting of ellipses to scattered data. The proposed algorithm makes use of well-known techniques that improve the robustness of the direct least-square fitting with a modest increase of the computational burden. Furthermore, by trivial modifications of the constrained minimization problem the algorithm may be converted to perform the specific fitting of other types of conics such as hyperbola. The method is simple and accurate and can be implemented with fixed time of computation. These characteristics coupled to its robustness and specificity makes the algorithm well-suited for applications requiring real-time machine vision.

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