A major issue in rehabilitation robotics is the fact that motor improvements following training with a robotic device are not observed in daily life, that is, when patients are not using the training device. This limited efficacy of robotic training is possibly due to unnatural human-machine interactions experienced when patients use the device. This Faculty Early Career Development (CAREER) Program project investigates robot-assisted motor learning in people with and without brain lesions. The aim is to improve effective gait rehabilitation after stroke by determining how to maximize generalization of learning from trained to untrained conditions. The PI will also use the research objectives in this project as a means to increase the participation of students from underrepresented minorities (URM) in science and engineering. Specifically, the PI will recruit, mentor, and prepare URM students from K-12 and college to pursue advanced education, with the ultimate goal of broadening the professional opportunities for URM students.
Split-belt walking, during which the legs move at different speeds, has been shown to induce locomotor learning in post-stroke patients and subjects without neurological damage. Here the PI will determine if the learning phase on the split-belt treadmill in these two populations can be altered to enhance the generalization of learned movements from the treadmill to natural walking. The research uses a human-in-the-loop method that manipulates a subject's perceived gait symmetry to create the illusion of error-free performance during split-belt walking. Through this closed-loop approach, the PI aims to identify ways to enhance the generalization of movements learned on the treadmill to non-treadmill conditions. If successful, the project could have a transformative effect on procedures for gait rehabilitation after stroke.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
