Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements - a pilot study.

ABSTRACT:

Background

Intensive robot-assisted training of the upper limb after stroke can reduce motor impairment, even at the chronic stage. However, the effectiveness of practice for recovery depends on the selection of the practised movements. We hypothesized that rehabilitation can be optimized by selecting the movements to be practiced based on the trainee's performance profile.

Methods

We present a novel principle ('steepest gradients') for performance-based selection of movements. The principle is based on mapping motor performance across a workspace and then selecting movements located at regions of the steepest transition between better and worse performance. To assess the benefit of this principle we compared the effect of 15 sessions of robot-assisted reaching training on u

SUBMITTER: Rosenthal O 

PROVIDER: S-EPMC6425657 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature