光学技术, 2019, 45 (2): 129, 网络出版: 2019-04-28  

基于非线性力反馈的血管介入手术训练系统

Interventional vascular surgery training system based on nonlinear force feedback
作者单位
北京理工大学 光电技术与信息系统实验室, 北京 100081
摘要
血管介入手术训练系统是利用虚拟现实技术帮助医生学员快速、高效、低成本地掌握血管介入手术技能的训练系统。由于国外商业产品存在较高技术壁垒且我国对本课题的研究起步较晚, 导致系统存在血管形变仿真缺失、力反馈计算方法简单等诸多不足。针对这些问题研发了一套血管介入手术虚拟训练系统, 实现了系统的血管与导丝柔性形变、血管碰撞检测、力反馈计算与导丝运动控制等功能。分别基于张量有限元和杆单元有限元构建了血管和导丝的物理模拟模型; 研究了血管与导丝模型的碰撞检测方法; 通过导丝前端碰撞模型与血管壁碰撞模型间的接触面积构造非线性力学方程, 提出了非线性力反馈计算方法。实验结果表明, 系统中血管张量有限元物理模型具有良好的柔性形变效果, 为系统提供了较好的视觉反馈信息; 非线性力反馈计算方法更好的模拟了导丝与血管间作用力的特性; 系统实现了手术训练功能, 并具有良好的实时性。
Abstract
The interventional vascular surgery virtual training system is designed for improving doctors’ skills quickly, efficiently and cost-effectively by using virtual reality technology. Researches on this topic in China started later than other developed countries and are still in the R&D stage of the prototype. Productization and commercialization hasn’t been realized. Based on this, a virtual training system is developed for vascular intervention based on nonlinear force feedback method. The physical simulation models for blood vessels and guidewires are constructed based on finite element model of tensor and rod element, respectively. The collision detection method for blood vessels and guide wires is studied. Using the collision area between the leading end of the guide wire and the blood vessel wall, a nonlinear mechanical equation is constructed and a nonlinear force feedback calculation method is proposed. Then, the main functional modules such as collision detection, flexible deformation and force feedback calculation of the virtual system for vascular interventions are realized. The developed interventional vascular surgery training system was evaluated and experimental results show that the system is of real-time response and fidelity.

陈铁凝, 康瑞瑞, 朱建军, 黄勇, 杨健. 基于非线性力反馈的血管介入手术训练系统[J]. 光学技术, 2019, 45(2): 129. CHEN Tiening, KANG Ruirui, ZHU Jianjun, HUANG Yong, YANG Jian. Interventional vascular surgery training system based on nonlinear force feedback[J]. Optical Technique, 2019, 45(2): 129.

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