Each year, about 700,000 people in the United States have a stroke, making it a leading cause of serious, long-term disability. Modalities of therapy often assume the processes underlying motor recovery and motor learning are similar because both exhibit activity- dependent neural plasticity. However, the impact of other factors unique to recovery such as re-acquisition of muscle strength and resolution of abnormal muscle tone confounds the validity of this assumption. By implementing an adaptive impedance controller that collapses from a "virtual slot" between two targets to a "virtual spring" at the desired target, a new performance-based progressive therapy (PBPT) algorithm was developed to test whether recovery would be enhanced by incorporating learning strategies like repetition, goal specification, and positive reinforcement. A study of chronic stroke patients (8 to 95 months post-stroke) who were in a clinically verified "stable" phase of recovery was conducted with the PBPT protocol, in which patients made over 12,000 visually guided, point-to-point movements.
展开▼
