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About

Xiangyan Chen is a leading researcher in the field of medical robotics and fiber optic sensing, with a particular focus on shape reconstruction for minimally invasive surgical instruments. Her work centers on the development and application of Fiber Bragg Grating (FBG) sensors, enabling precise, real-time tracking of flexible tools used in complex procedures such as trans-oral laryngeal surgery, breast tumor needle puncture, and cardiac catheter navigation. Chen’s major contributions include pioneering the fabrication of thin-diameter, no-substrate FBG sensors that minimize invasiveness while maintaining high accuracy. Her 2020 paper on catheter shape detection (15 citations) and her 2021 study on position tracking accuracy (10 citations) are foundational, demonstrating how these sensors can overcome limitations in end-position and shape reconstruction. She has further advanced the field by addressing strain transfer characteristics (9 citations) and developing novel reconstruction methods that compensate for twisting in flexible robots (2024). Chen’s work on an FBG sensor for a trans-oral laryngeal surgery robot (2019) exemplifies her commitment to translating sensor technology into practical surgical tools. With a growing citation record and a focus on solving real-world clinical challenges, Chen is shaping the future of smart, sensor-driven surgical robotics.