Robotic rehabilitation for people who have suffered from stroke or spinal cord injuries can provide consistent, measured, and repetitive therapy. Although excellent hardware for both upper and lower limb robotic rehabilitation already exists, there are concerns over how humans interact with this hardware. In particular, robots need to (a) encourage active subject participation during therapy, and (b) ensure subjects retain their improvements after the robot is removed.
My research on robotic rehabilitation is focused on developing control strategies which assist subjects without reducing their participation, as well as examining how these control strategies influence a subject’s long-term motor learning.
We hope that this research can improve the functional outcomes of robotic rehabilitation!
Schematic of robotic rehabilitation. On left, the human physically interacts with a robot while receiving kinesthetic, visual, and auditory feedback. By moving the robot, the human causes a cursor to move within the virtual environment (on right). Here the human attempts to track a desired trajectory while avoiding obstacles, and the feedback is based on his performance. My research investigates what forces the robot should apply to assist the subject, and what types of feedback should be provided.
Publications on Robotic Rehabilitation
- A. U. Pehlivan*, D. P. Losey*, and M. K. O’Malley, “Minimal assist-as-needed controller for upper limb robotic rehabilitation,” IEEE Transactions on Robotics, vol. 32, no. 1, pp. 113-124, 2016. PDF.
- D. P. Losey, L. H. Blumenschein, and M. K. O’Malley, “Improving the retention of motor skills after reward-based reinforcement by incorporating haptic guidance and error augmentation,” Proc. IEEE RAS/EMBS Int. Conf. on Biomedical Robotics and Biomechatronics (BioRob), pp. 865-871, 2016. PDF.
Many of my peers within the MAHI Lab are also interested in rehabilitation devices, protocols, and experiments. You can learn more about the newly built Rice OpenHand here.