Matteo Lancini
Papers
11
Total Citations
245
H-Index
8
About
Matteo Lancini is a researcher at the forefront of human-robot interaction, specializing in exoskeletons, collaborative robotics, and rehabilitation systems. His work bridges mechanical design, deep learning, and safety engineering to create intuitive, human-centered robotic technologies. Lancini’s most cited paper, “Characterization and Evaluation of Human–Exoskeleton Interaction Dynamics: A Review” (68 citations), provides a critical framework for understanding physical human-exoskeleton interaction, essential for medical and industrial device compliance. He has pioneered hand gesture recognition for collaborative robots using Faster R-CNN deep learning (53 citations), enabling more natural human-robot communication. His contributions extend to rehabilitation robotics, including an EMG-driven hand mirroring system (26 citations) and the ERRSE elbow rehabilitation system with force control (19 citations). Lancini also advanced industrial safety with a vision-based system using Time-of-Flight cameras for point cloud analysis (13 citations) and developed methods for cobot user frame calibration (21 citations). His recent work on knee exoskeleton misalignment compensation (2023) demonstrates ongoing innovation in wearable robotics. With over 240 total citations across these key papers, Lancini’s research is shaping safer, more effective human-robot collaboration and rehabilitation technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2Deep learning-based hand gesture recognition for collaborative robots53 citations · 2019
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- 6ERRSE: Elbow Robotic Rehabilitation System with an EMG-Based Force Control19 citations · 2017
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- 9Monitoring Upper Limbs During Exoskeleton-Assisted Gait Outdoors4 citations · 2018
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