Giulio Iannello
Papers
7
Total Citations
74
H-Index
4
About
Giulio Iannello’s research sits at the intersection of neural engineering, rehabilitation robotics, and medical imaging, with a focus on restoring function and improving clinical outcomes. He has made significant contributions to understanding how intraneural interfaces can modulate sensorimotor integration in amputees, as demonstrated by his highly cited 2014 EEG-TMS study on robotic hand control (24 citations). His work in rehabilitation robotics includes developing a modular telerehabilitation architecture for upper limb therapy and, most recently, the AI-CARE project (2025), which leverages artificial intelligence for customized, adaptive robot-aided rehabilitation. Iannello has also advanced the field of radiomics, pioneering early methods to predict CyberKnife treatment response in acoustic neuroma using machine learning—a series of studies that have collectively garnered over 16 citations. Additionally, his pattern recognition approach to detecting human movement onset from force measurements (22 citations) has practical applications in assistive technology. Through these diverse but interconnected lines of work, Iannello has demonstrated how computational methods can enhance both neural interfacing and personalized medicine, making his research highly relevant for students and researchers interested in neurorehabilitation, AI in healthcare, and biomedical signal processing.
Research Focus
Key Achievements
Top Papers
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- 3A modular telerehabilitation architecture for upper limb robotic therapy9 citations · 2017
- 4Tackling imbalance radiomics in acoustic neuroma8 citations · 2019
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