Lorenzo Amato
Papers
2
Total Citations
6
H-Index
2
About
Lorenzo Amato is a rising researcher in the field of rehabilitation robotics and human-robot interaction, with a focus on assistive exoskeletons and motor coordination. His work centers on two key areas: decoding movement intention for upper-limb assistance, and enhancing motor synchrony in human-robot-human (HRH) collaboration. In his 2023 proof-of-concept study, Amato developed an adaptive dynamic movement primitive algorithm that decodes reaching intentions to control a 4-DOF shoulder-elbow exoskeleton, offering a promising pathway for assisting users with upper-limb impairments who retain some movement initiation ability. This work, with 4 citations, establishes a foundation for intuitive, user-driven robotic support. More recently, in 2025, Amato explored the emerging paradigm of HRH interaction, demonstrating how portable elbow exoskeletons can enhance motor synchrony in rhythmic dyadic tasks. With 2 citations, this contribution highlights the potential of wearable robots to improve cooperative physical interactions between humans. Amato’s research bridges neural decoding, adaptive control, and social motor coordination, positioning him as a forward-thinking contributor to assistive robotics and collaborative human-machine systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2