Lucia Schiatti
Papers
2
Total Citations
30
H-Index
2
About
Lucia Schiatti is a leading researcher at the intersection of assistive robotics, brain-machine interfaces, and human-robot interaction. Her work focuses on developing intelligent, user-centered control systems that empower individuals with severe motor disabilities. Schiatti’s major contribution lies in pioneering "human-in-the-loop" frameworks that leverage electrophysiological signals—such as EEG-based error detection—to create more intuitive and responsive robotic devices. Her highly cited 2018 paper (20 citations) demonstrates how shared control can be enhanced by using the user’s own neural reward signals to guide robot learning, effectively reducing cognitive burden while improving task performance in target identification and reaching. In her 2017 work (10 citations), she introduced a novel "soft" control approach for brain-machine interfaces, emphasizing the use of residual motor functions to create seamless, adaptive assistive technologies. By bridging neuroscience and robotics, Schiatti’s research not only advances the theoretical understanding of shared autonomy but also offers practical pathways toward greater independence for people with motor impairments. Her work is foundational for students and researchers exploring non-invasive, EEG-driven control in real-world assistive applications.
Research Focus
Key Achievements
Top Papers
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