Preliminary results from a stroke rehabilitation protocol utilizing a robotic BMI-exoskeleton system

Effective strategies for stimulating motor learning post-stroke involve large dosages of movement repetitions, during which patients are engaged both physically and mentally. While robots are inherently suitable for rehabilitation due to their ability to provide intensive movement training and precise measurement, it is less obvious how to ensure patient focus and mental engagement during therapy. To address this limitation, we have augmented an upper-limb robotic exoskeleton, the MAHI Exo-II, with a brain-machine interface (BMI) that monitors EEG signals to detect movement intention in real time. We present preliminary findings of a 12-session stroke rehabilitation protocol utilizing this BMI-Exo system for elbow flexion-extension training.