Davide Di Febbo
Papers
1
Total Citations
4
H-Index
1
About
Davide Di Febbo is a researcher at the intersection of rehabilitation robotics and artificial intelligence, whose work focuses on restoring motor function in stroke survivors. His primary research areas include functional electrical stimulation (FES), reinforcement learning (RL) control systems, and hybrid robotic exoskeletons for upper limb rehabilitation. Di Febbo’s major contribution lies in pioneering the application of RL to design non-linear controllers for FES, addressing a critical limitation in current rehabilitation technology—the inability to produce smooth, natural movements of the paretic arm. His 2018 feasibility study, which has garnered 4 citations, demonstrated that RL-based controllers can effectively coordinate electrical stimulation with robotic support, offering a more adaptive and patient-specific approach to therapy. This work represents a significant step toward intelligent, autonomous rehabilitation systems that learn and adjust in real-time. Di Febbo’s research holds promise for improving the quality of life for individuals with neurological impairments, and his innovative use of machine learning in assistive technology continues to inspire new directions in neurorehabilitation engineering.
Research Focus
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Top Papers
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