Fernando Trejo
Papers
2
Total Citations
7
H-Index
2
About
Fernando Trejo is a researcher at the forefront of surgical simulation and haptic interaction, whose work bridges the critical gap between virtual environments and real-world surgical training. His primary research areas include haptic modeling for soft-tissue dissection and the ergonomic design of robot-assisted surgical systems. Trejo’s major contribution lies in developing analytic haptic models for force rendering during tool-tissue interaction, specifically addressing the underexplored area of soft-tissue dissection—a process more complex than simple indentation or cutting. His 2016 paper on this topic, with 5 citations, provides foundational insights for creating more realistic and responsive haptic feedback in surgical simulators. Additionally, his 2018 study on user performance in VR-based dissection, cited 2 times, investigates the challenges of motion-coupling in robotic systems, comparing it to direct mapping to understand how these interfaces affect surgeon learning curves. By tackling the slow adoption of robot-assisted systems, Trejo’s work is instrumental in enhancing the intuitiveness and effectiveness of surgical training tools, ultimately aiming to improve patient outcomes through better-prepared surgeons.
Research Focus
Key Achievements
Top Papers
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