Adaptive assistance for guided force training in chronic stroke

This work describes a novel form of robotic therapy for the upper extremity in chronic stroke. Based on previous results, we hypothesized that a training task that encourages subjects to consciously guide endpoint forces generated by the hemiparetic arm will result in significant gains in functional ability of the arm, superior to more conventional methods of therapy. In addition, since stroke survivors present with varying degrees of arm movement ability, we developed an adaptive algorithm that tailors the amount of assistance provided in completing the guided force training task. The algorithm adapts a coefficient for velocity-dependent assistance based on measured movement speed, on a trial-to-trial basis. The training algorithm has been implemented with a simple linear robotic device called the ARM Guide. One participant completed a two month training program with the adaptive algorithm, resulting in significant improvements in the performance of functional tasks.