Dissociating motor learning from recovery in exoskeleton training post-stroke.

ABSTRACT:

Background

A large number of robotic or gravity-supporting devices have been developed for rehabilitation of upper extremity post-stroke. Because these devices continuously monitor performance data during training, they could potentially help to develop predictive models of the effects of motor training on recovery. However, during training with such devices, patients must become adept at using the new "tool" of the exoskeleton, including learning the new forces and visuomotor transformations associated with the device. We thus hypothesized that the changes in performance during extensive training with a passive, gravity-supporting, exoskeleton device (the Armeo Spring) will follow an initial fast phase, due to learning to use the device, and a slower phase that corresponds to redu

SUBMITTER: Schweighofer N 

PROVIDER: S-EPMC6173922 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature