A Real-Time Haptic/Graphic Demonstration of how
Error Augmentation can Enhance Learning
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Yejun Wei and James Patton Sensory Motor Performance Program Rehabilitation Institute of Chicago Northwestern University Chicago, IL 60611 |
Preeti Bajaj Johns Hopkins University Biomedical Engineering Baltimore, MD 21210
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Robert Scheidt Dept. Biomedical Engineering Marquette University Milwaukee, WI |
Abstract – We developed a real-time controller for a 2 degree-of-freedom robotic system using xPC Target. This
system was used to investigate how different methods of performance error feedback can lead to faster and more
complete motor learning in individuals asked to compensate for a novel visuo-motor transformation (a 30 degree rotation).
Four groups of human subjects were asked to reach with their unseen arm to visual targets surrounding a central starting
location. A cursor tracking hand motion was provided during each reach. For one group of subjects, deviations from the
“ideal” compensatory hand movement (i.e. trajectory errors) were amplified with a gain of 2 whereas another group was
provided visual feedback with a gain of 3.1. Yet another group was provided cursor feedback wherein the cursor was rotated
by an additional (constant) offset angle. We compared the rates at which the hand paths converged to the steady -state
trajectories. Our results demonstrate that error-augmentation can improve the rate and extent of motor learning of
visuomotor rotations in healthy subjects. Furthermore, our results suggest that both error amplification and offsetaugmentation
may facilitate neurorehabilitation strategies that restore function in brain injuries such as stroke.
Index Terms – neuro-robotics, error augmentation, xPC
Target, motor learning, and visual distortion