Javier Cuadrado
Papers
8
Total Citations
156
H-Index
5
About
Javier Cuadrado is a distinguished researcher whose work spans two interconnected domains: computational multibody dynamics and assistive robotics for rehabilitation. In multibody systems, Cuadrado has made foundational contributions to real-time dynamic formulations, developing innovative approaches that combine penalty and recursive methods to enable efficient simulation of complex mechanical systems — including full automobile models — on standard personal computers. His 2004 paper on this combined formulation remains his most influential work, amassing 75 citations, while subsequent contributions explored parallel index-3 formulations and hybrid global-topological approaches that further advanced computational efficiency. Cuadrado's research evolved meaningfully toward biomedical applications, particularly the design and control of robotic exoskeletons for spinal cord injury rehabilitation. His 2019 study on a lightweight, modular walking assistance exoskeleton has garnered 40 citations, reflecting growing community interest in accessible rehabilitation technology. Projects like ABLE — an assistive biorobotic low-cost exoskeleton — demonstrate his commitment to making such devices practical and affordable beyond clinical settings. His editorial leadership on virtual sensing integration and participation in IUTAM symposia further underscore his role as a connector between computational modeling and real-world engineering applications, making him an influential figure across mechanical simulation and rehabilitation engineering communities.
Research Focus
Key Achievements
Top Papers
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- 5A Hybrid Global-Topological Real-Time Formulation for Multibody Systems8 citations · 2003
- 6ABLE: assistive biorobotic low-cost exoskeleton5 citations · 2017
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