Papers
56
Total Citations
653
H-Index
15
About
Paul Tucan is a prominent robotics researcher whose work sits at the intersection of mechanical engineering, medical robotics, and artificial intelligence. He has made significant contributions to the design, analysis, and clinical application of parallel robotic systems, with a particular focus on neurological rehabilitation and surgical assistance. His 2019 algebraic parameterization work (39 citations) established foundational methods for analyzing parallel robot mechanics, while his RAISE system (2018) pioneered innovative lower limb rehabilitation platforms. Tucan has been especially influential in advancing safety frameworks for medical robots, applying fuzzy logic and risk-based engineering methodologies to ensure patient protection during rehabilitation — work that has collectively earned over 70 citations across two key studies. His research bridges engineering and clinical neuroscience, demonstrated by collaborative neurophysiological assessments of robotic rehabilitation outcomes in stroke and neuromuscular disease patients. More recently, Tucan has expanded into oncological applications, developing brachytherapy robotic instruments and AI-driven hazard detection for minimally invasive surgery. With over 300 cumulative citations across his most impactful papers, his interdisciplinary portfolio positions him as a leading voice in the rapidly evolving field of medical robotics.
Research Focus
Key Achievements
Top Papers
- 1An algebraic parameterization approach for parallel robots analysis39 citations · 2019
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- 10RAISE - An Innovative Parallel Robotic System for Lower Limb Rehabilitation27 citations · 2018