Papers
8
Total Citations
289
H-Index
5
About
Fiorenzo Artoni is a leading researcher at the intersection of neural engineering, rehabilitation robotics, and human-machine interaction. His work focuses on decoding neural and muscular signals to create intuitive, proportional control systems for assistive technologies. Artoni’s most impactful contribution is the development of a shared human–robot proportional control framework for dexterous myoelectric prostheses (146 citations), which allows amputees to achieve natural, simultaneous finger movements. He also pioneered a data-driven body–machine interface for accurate drone teleoperation (91 citations), demonstrating how simple, reliable control can be achieved without extensive training. In rehabilitation, Artoni has advanced EEG-based monitoring during robotic gait training (e.g., Lokomat), showing how cortico-muscular connectivity is modulated by passive and active assistance. His work on motor intention decoding during robot-assisted reaching and EEG prediction of upper limb recovery in chronic stroke patients has opened new pathways for personalized neurorehabilitation. By combining deep learning with surface EMG recordings, Artoni continues to push the boundaries of proportional finger control for prosthetic hands, making him a key figure in the quest for seamless, brain-machine interfaces.
Research Focus
Key Achievements
Top Papers
- 1Shared human–robot proportional control of a dexterous myoelectric prosthesis146 citations · 2019
- 2Data-driven body–machine interface for the accurate control of drones91 citations · 2018
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- 6Motor Intention Decoding During Active and Robot-Assisted Reaching3 citations · 2018
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- 8EEG Decoding of Overground Walking and Resting, a Feasibility Study2 citations · 2018