Robot-assisted arm training in physical and virtual environments: A case study of long-term chronic stroke

Abstract

Robot-assisted training (RT) is a novel technique with promising results for stroke rehabilitation. However, benefits of RT on individuals with long-term chronic stroke have not been well studied. For this case study, we developed an arm-based RT protocol for reaching practice in physical and virtual environments and tracked the outcomes in an individual with a long-term chronic stroke (20+ years) over 10 half-hour sessions. We analyzed the performance of the reaching movement with kinematic measures and the arm motor function using the Fugl-Meyer Assessment-Upper Extremity scale (FMA-UE). The results showed significant improvements in the subject's reaching performance accompanied by a small increase in FMA-UE score from 18 to 21. The improvements were also transferred into real life activities, as reported by the subject. This case study shows that even in long-term chronic stroke, improvements in motor function are still possible with RT, while the underlying mechanisms of motor learning capacity or neuroplastic changes need to be further investigated.