Lorenzo Grazi
Papers
9
Total Citations
327
H-Index
7
About
Lorenzo Grazi is a leading researcher in wearable robotics and human-robot interaction, with a focus on developing intelligent control systems for assistive exoskeletons. His work spans upper-limb, hip, and low-back exoskeletons, with a particular emphasis on using surface electromyographic (sEMG) signals to detect user movement intentions and enable intuitive, real-time assistance. Grazi’s most cited paper (155 citations) pioneered the detection of movement onset via EMG for upper-limb exoskeletons in reaching tasks, a foundational contribution to shared control in rehabilitation robotics. He also advanced adaptive control methods for discrete movements like lifting (46 citations) and developed a novel myoelectric control strategy using gastrocnemius signals to assist hip flexion (33 citations), reducing lower-limb muscle activity during push-off. His work on low-back exoskeletons (27 citations) demonstrated significant reductions in erector spinae activity during lifting, addressing critical ergonomic challenges in industry. More recently, Grazi has explored human-robot-human interaction to enhance motor synchrony in dyadic tasks, and contributed to the Mari4_YARD project, bringing advanced robotic solutions to small and medium shipyards. With over 300 total citations and a growing portfolio of high-impact studies, Grazi is shaping the future of wearable assistive technology for both rehabilitation and industrial applications.
Research Focus
Key Achievements
Top Papers
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- 6Gastrocnemius myoelectric control of a robotic hip exoskeleton15 citations · 2015
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