AbstractRecent technological developments are allowing rehabilitation practitioners to use robotic therapies and haptic interfaces to support clients in (re)learning motor skills. However, reports of effectiveness have been inconsistent and many of the underlying concepts are not fully understood. A better understanding of the relevant motor learning principles in healthy individuals may help to advance practice in the rehabilitative context. Haptic training researchers are now designing systems and conducting experiments to explore the benefits of learning with and without the experience of errors. Even though this question of the role of errors in motor learning is an old one, there is no widely accepted answer. While haptic training has traditionally employed error-minimization (“errorless practice”) approaches, haptic interface systems can typically provide not only regular practice of a task but “errorful” practice conditions in which errors are visually and/or haptically augmented. However, there has been no comprehensive evaluation of errorless and errorful learning approaches for haptic training of tracing – a closed-loop, self-paced task. We conducted two experiments to determine how these two approaches impact on learning a contour-tracing task. In the first experiment, we compared conditions of error-minimizing and error-augmenting haptic feedback with naturally occurring errors. Analysis of movement time and tracing error demonstrated that while error-minimization produced superior performance during practice, this group fared worst on transfer tests. Further, there were no differences in learning between the two groups that experienced errors (regular practice and error-augmented practice). In the second experiment, we are comparing conditions of error-minimizing and error-augmenting haptic feedback, each provided under two tolerances for error (tight and wide bandwidths). Data collection is on-going. We relate our findings from experiment 1 to the role of errors in motor learning and issues of feedback frequency and task difficulty.
Acknowledgments: This research was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC).