A number of rehabilitation robots were developed and used to promote the recovery of motor functions in the upper extremities of stroke patients. Current clinical evidence suggests that the robotic rehabilitation is much more effective in acute than in chronic patients. One important difference between the two groups is the amount of the baseline skills with which they start the training. The goal of our research was to get a further insight into this issue by conducting an experiment in healthy subjects. As a model of motor learning, simulating the process of robotic rehabilita-tion, we developed a methodology for the transfer of a motor skill from an expert to a novice subject by using a haptic interface integrated with the virtual environment. A motor skill was implemented in the form of a challenging computer game, and the haptic interface provided the assistive forces during playing. To assess if and how a level of prior skills affects the motor learning assisted by the robot, the game was played by both novice and partially trained players. The results showed that the assistance was effective only in the novice players, while the trained players experienced the assistive forces as a disturbance. In the context of neurorehabilitation, this finding implies that the existing experience of chronic patients, i.e., the established motor patterns (e.g., compensatory strategies), has to be considered when designing the assistance that would actually promote (instead of disturbing) the learning process.

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