Pegah Yaftian
Papers
2
Total Citations
17
H-Index
2
About
Pegah Yaftian is a researcher at the forefront of soft robotics and medical device innovation, specializing in enhancing the safety and efficacy of robot-assisted surgical procedures. Her primary research focuses on real-time force estimation for tendon-driven soft robotic catheters, a critical challenge in radio frequency ablation (RFA) treatments. Yaftian’s major contributions include developing an image-based method for contact detection and static force estimation on steerable catheters, detailed in her most-cited work (11 citations, 2020). This approach enables real-time feedback without requiring additional sensors, directly improving procedural safety. She further advanced the field by systematically comparing mechanistic and learning-based models for tip force estimation (6 citations, 2022), providing key insights into the trade-offs between accuracy and computational efficiency. Her work bridges the gap between theoretical modeling and practical clinical application, offering a roadmap for integrating soft robotic catheters into minimally invasive surgery. With a growing citation record and a focus on translating robotics into tangible medical solutions, Yaftian is establishing herself as a rising voice in surgical robotics, where her research promises to make complex procedures safer and more accessible.
Research Focus
Key Achievements
Top Papers
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