Key components of mechanical work predict outcomes in robotic stroke therapy.
Journal:
Journal of neuroengineering and rehabilitation
Published Date:
Apr 21, 2020
Abstract
BACKGROUND: Clinical practice typically emphasizes active involvement during therapy. However, traditional approaches can offer only general guidance on the form of involvement that would be most helpful to recovery. Beyond assisting movement, robots allow comprehensive methods for measuring practice behaviors, including the energetic input of the learner. Using data from our previous study of robot-assisted therapy, we examined how separate components of mechanical work contribute to predicting training outcomes.