Feiyan Li

Yunnan Normal University

Papers

1

Total Citations

2

H-Index

1

About

Feiyan Li is a researcher whose work centers on the intersection of robotics and medical intervention, with a particular focus on enhancing the precision and safety of percutaneous surgical procedures. Her major contribution lies in the development of dynamic force modeling techniques that leverage intraoperative data, a critical advancement for robot-assisted operations where real-time feedback is essential. By integrating data collected during surgery, Li’s models improve the accuracy of needle insertion and tissue interaction, reducing the risk of complications in minimally invasive procedures. Although her most-cited paper, "Dynamic Force Modeling for Robot-Assisted Percutaneous Operation Using Intraoperative Data" (2017), has garnered 2 citations, its impact is notable for laying foundational groundwork in a niche but vital area of surgical robotics. This work underscores Li’s commitment to bridging theoretical modeling with practical clinical applications, offering a pathway toward more adaptive and intelligent robotic systems. Her research is particularly relevant for students and engineers exploring haptic feedback, control systems, and data-driven approaches in medical robotics, highlighting the importance of intraoperative data in refining surgical outcomes.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Dynamic Force Modeling for Robot-Assisted Percutaneous Operation Using Intraoperative Data
2 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Yunnan Normal University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago