The goal of this project is to improve robotic neurorehabilitation by developing robotic artificial intelligence, which can automatically adapt the robotic training strategy to the trainee’s special needs and the trained motor task, and improve its strategy over time.
Research on neurorehabilitation has emphasized that patient’s effort and somatosensory information (i.e., the information about the interaction with the environment) during physical training are crucial to provoke brain plasticity. This project aims to develop a novel clinical-driven and cost-effective upper limb rehabilitation robot in order to promote simultaneously sensor and motor recovery in neurological patients with a large range of disability levels and different stages of recovery.
Robot-aided gait rehabilitation is a promising technique to improve rehabilitation in patients with neurological injuries. The goal of this project is to evaluate the effect of haptic error modulating controllers on relearning to walk.