Diego Guffanti

Universidad UTE, Universidad Politécnica de Madrid

Papers

9

Total Citations

68

H-Index

4

About

Diego Guffanti is a robotics and biomedical engineering researcher whose work sits at the intersection of mobile robotics, human gait analysis, and machine learning. He is best known for developing ROBOGait, a ROS-based mobile robotic platform designed to monitor and analyze human gait in clinical environments — a novel integration that has earned his foundational 2021 papers 18 citations each, signaling strong early impact in the field. Guffanti's research addresses a critical limitation of traditional gait analysis: the restricted walking distances imposed by fixed laboratory setups. By mounting 3D depth cameras onto autonomous robots, he enables continuous, markerless gait assessment across natural corridor environments, making the technology far more accessible for clinical use. To overcome the inherent accuracy limitations of consumer-grade 3D cameras, he has applied supervised learning and artificial neural networks to refine gait measurements, with notable case studies in Multiple Sclerosis patients. Beyond gait analysis, Guffanti has demonstrated broader mechatronic expertise through the design of a dexterous robotic hand for gestural communication, cited 11 times since 2023. His growing body of work positions him as an emerging contributor to rehabilitation robotics and intelligent human movement assessment.

Research Focus

Key Achievements

4
H-Index
9
Papers
68
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Development and validation of a ROS-based mobile robotic platform for human gait analysis applications
18 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 25
🏛 Institutions: Universidad UTE, Universidad Politécnica de Madrid

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago