Automated Feedback Selection for Robot-Assisted Training

Abstract

Robot-assisted training can be enhanced by using augmented feedback to support trainees during learning. Efficacy of augmented feedback is assumed to be dependent on the trainee's skill level and task characteristics. Thus, selecting the most efficient augmented feedback for individual subjects over the course of training is challenging.

Keywords

• virtual trainer
• rowing simulator
• motor learning
• linear mixed models
• statistical learning