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Stroke can severely limit a person's ability to move their arm, especially when trying to reach by extending the elbow. These challenges often persist long after the stroke and make everyday activities more difficult. The investigators are testing a feedback strategy called error augmentation (EA) feedback that intentionally exaggerates movement errors to promote motor learning.
In this study, the investigators designed a virtual reality training program that uses EA feedback to encourage people with chronic stroke to use more elbow extension during reaching. The EA feedback makes it appear as though the elbow is more bent than it actually is, prompting the participant to extend their elbow further than they normally would. By having the patient practice movement with enhanced feedback, the investigators predict that the patient will increase the range of motion and improve reaching ability.
This is a short, proof-of-concept study to evaluate whether EA feedback shows early promise for improving arm movement in people with upper limb motor impairment after stroke. Participants are randomly assigned to either an EA training group or a control group (no-EA feedback). Each person completes three 30-minute virtual reality training sessions over 1 week. The investigators assess arm movement and motor impairment before and after training, and again one hour after the training to determine if improvements are retained.
Findings from this preliminary study will help determine whether this EA-based training approach should be used in a longer 9-week clinical trial aimed at promoting long-term recovery of arm function after stroke.
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28 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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