Nonlinear Viscoelastic Model-based Deformation Optimization for Robotic Micropuncture in Retinal Vein Cannulation
Bo Hu, Ruimin Li, Shiyu Xu, Rongxin Liu, Zengshuo Wang, Mingzhu Sun, Xin Zhao
Abstract
Micropuncture is a critical step in drug injection during retinal vein cannulation (RVC) surgery. Minimizing deformation during the micropuncture process is beneficial to reduce mechanical damage. However, this goal is challenging due to the viscoelastic characteristics of retinal tissue. In this paper, a robotic micropuncture scheme for deformation optimization that incorporates a nonlinear force model is proposed. Before micropuncture, a preload strategy is utilized to ensure stable contact between needle and retinal vein. Secondly, a nonlinear viscoelastic (NV) model is developed to characterize the nonlinearity and relaxation behavior of the tissue. Finally, a speed optimization framework, based on the NV model and physical constraint, is adopted to minimize deformation. The effectiveness of the proposed scheme is validated through in vitro experiments conducted on open-sky porcine eyes. With average force error of 1.48 μN, stable contact can be achieved via proportion-integral-differential controller. The experimental results demonstrate that the NV model is more suitable for force modeling of retinal tissue. Furthermore, the optimized speed results in an average deformation of 0.5727 mm, which represents a reduction of at least 21.02% compared to the linear model. Thanks to the proposed scheme, the robotic micropuncture based on a varying speed trajectory can reduce deformation and enhance the safety of RVC surgery.
BibTeX
@inproceedings{iros2025_nonlinearviscoel,
title = {Nonlinear Viscoelastic Model-based Deformation Optimization for Robotic Micropuncture in Retinal Vein Cannulation},
author = {Bo Hu and Ruimin Li and Shiyu Xu and Rongxin Liu and Zengshuo Wang and Mingzhu Sun and Xin Zhao},
booktitle = {IROS 2025},
year = {2025}
}