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[血管介入机器人导管输送力实时检测系统研究]

[Research on real-time detection system of catheter delivering force in vascular interventional robots].

作者信息

Li Hui, Zhou Hao, Zhao Yan, Zhang Jianhua, Zhang Tianjing

机构信息

The School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, P. R. China.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2022 Apr 25;39(2):359-369. doi: 10.7507/1001-5515.202109080.

Abstract

In existing vascular interventional surgical robots, it is difficult to accurately detect the delivery force of the catheter/guidewire at the slave side. Aiming to solve this problem, a real-time force detection system was designed for vascular interventional surgical (VIS) robots based on catheter push force. Firstly, the transfer process of catheter operating forces in the slave end of the interventional robot was analyzed and modeled, and the design principle of the catheter operating force detection system was obtained. Secondly, based on the principle of stress and strain, a torque sensor was designed and integrated into the internal transmission shaft of the slave end of the interventional robot, and a data acquisition and processing system was established. Thirdly, an ATI high-precision torque sensor was used to build the experimental platform, and the designed sensor was tested and calibrated. Finally, sensor test experiments under ideal static/dynamic conditions and simulated catheter delivery tests based on actual human computed tomography (CT) data and vascular model were carried out. The results showed that the average relative detection error of the designed sensor system was 1.26% under ideal static conditions and 1.38% under ideal dynamic stability conditions. The system can detect on-line catheter operation force at high precision, which is of great significance towards improving patient safety in interventional robotic surgery.

摘要

在现有的血管介入手术机器人中,难以在从动端精确检测导管/导丝的输送力。为了解决这个问题,基于导管推力为血管介入手术(VIS)机器人设计了一种实时力检测系统。首先,分析并建立了介入机器人从动端导管操作力的传递过程模型,得出了导管操作力检测系统的设计原理。其次,基于应力和应变原理,设计了一种扭矩传感器并将其集成到介入机器人从动端的内部传动轴中,并建立了数据采集与处理系统。第三,使用ATI高精度扭矩传感器搭建实验平台,对所设计的传感器进行测试和校准。最后,进行了理想静态/动态条件下的传感器测试实验以及基于实际人体计算机断层扫描(CT)数据和血管模型的模拟导管输送测试。结果表明,所设计的传感器系统在理想静态条件下的平均相对检测误差为1.26%,在理想动态稳定条件下为1.38%。该系统能够高精度地在线检测导管操作力,这对于提高介入机器人手术中的患者安全性具有重要意义。

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