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Consideration of human skill is necessary to enhance total performance of human-machine system and to assist the human operation. We guess that human skill level may be evaluated by checking the task scheduling of the operator on a general machine manipulation. Based on this hypothesis, in this paper, we propose a vision-based method to evaluate ability of human task-scheduling by monitoring a hand motion of a human operator who controls a machine console. This method utilizes a Kalman filter, and extracts hand's position by changing the detection threshold dynamically. It was confirmed that the tracking to the hand motion is done successfully. Furthermore, it was found that checking difference of predicted hand motion and actual motion, gives useful information about the micro-slip.