Proprioceptive Sinus Endoscopy: Calibrating Rigid Endoscope Bending with a Novel Strain-Sensing Sleeve
Endoscopic Sinus surgery (ESS) suffers from significant targeting inaccuracies due to elastic deformation of the rigid endoscope during vision-based surgical procedures. Current vision-based image-guided surgery systems assume rigid-body behavior, neglecting clinically significant deflections caused when surgeons use the endoscope shaft as a fulcrum against anatomical structures. To address this fundamental limitation, we present a novel real-time deformation compensation system featuring a compact, instrumented sleeve that mounts proximally on the endoscope shaft, external to the surgical field. The sleeve integrates six strain gauges distributed at two axial locations and employs a hybrid compliant mechanism design—combining flexure elements with lever-amplification mechanisms—to precisely capture multi-axis bending. We evaluated four mapping algorithms, including polynomial regression and machine learning approaches, to optimize displacement prediction. Our system reduced displacement error from ≈ 7mm to ≈ 1mm RMSE, achieving 85% improvement in target localization accuracy. This work introduces a practical, cost-effective solution that addresses a fundamental source of error in endoscopic navigation without disrupting established surgical workflows.
Authors
- zhifan yan
- Iulian Iordachita
- Masaru Ishii
- Manish Sahu
- Russell Taylor
Institutions
- Twitter (United States) (US)
Publication Details
- Journal
- Journal of Medical Robotics Research
- Published
- 2026-05-14
- DOI
- https://doi.org/10.1142/s2424905x2650008x
- Primary Topic
- Soft Robotics and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00