Leonardo Pollina
Papers
2
Total Citations
39
H-Index
2
About
Leonardo Pollina is pioneering the future of human-machine interaction, focusing on the frontiers of sensorimotor control and assistive robotics. His work bridges neuroscience and engineering to augment human capabilities, most notably through the development of extra robotic arms (XRAs). His landmark 2023 study, *Human motor augmentation with an extra robotic arm without functional interference* (27 citations), tackles the critical challenge of integrating a supernumerary limb into natural motor control without disrupting existing movements—a foundational step for practical augmentation. Pollina also advances the field of prosthetic control, employing deep learning with convolutional neural networks to decode finger movements from surface EMG signals. His 2021 work on proportional control (12 citations) directly addresses the difficulty of achieving simultaneous, intuitive control of robotic hands for amputees. By solving problems of neural interference and signal decoding, Pollina’s research is not only highly cited but is also shaping the next generation of wearable robotics and brain-machine interfaces, promising a future where humans can seamlessly control additional limbs and dexterous prosthetics.
Research Focus
Key Achievements
Top Papers
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