Andrea Parri

Piaggio (Italy), Scuola Superiore Sant'Anna

Papers

18

Total Citations

720

H-Index

12

About

Andrea Parri is a leading researcher in wearable robotics and human-robot interaction, with a focus on developing intelligent, bioinspired control systems for lower-limb exoskeletons and prostheses. His work centers on real-time gait phase estimation, balance recovery, and metabolic efficiency in assistive devices. Parri’s most cited paper (137 citations) introduces an oscillator-based method for smooth, real-time gait phase estimation, a foundational contribution to wearable robotics. He also demonstrated that an ecologically-controlled exoskeleton can improve balance after slippage (126 citations), and showed that gait training with a robotic hip exoskeleton enhances metabolic efficiency in the elderly (97 citations). Parri has pioneered novel control strategies using noncontact capacitive sensors and electromyographic signals, enabling more intuitive and ergonomic human-robot interaction. His research on real-time locomotion mode recognition (75 citations) and bioinspired motor primitives (56 citations) has advanced the field’s understanding of cooperative exoskeleton control. Parri’s work is distinguished by its emphasis on practical, user-centered design, with applications in rehabilitation, active aging, and assistive technology.

Research Focus

Key Achievements

12
H-Index
18
Papers
720
Total Citations
40
Avg Citations/Paper
🏆 Most Cited Paper
An oscillator-based smooth real-time estimate of gait phase for wearable robotics
137 citations · 2016
📈 Most Prolific Year: 2016 (4 Papers)
🤝 Key Collaborators: 78
🏛 Institutions: Piaggio (Italy), Scuola Superiore Sant'Anna

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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