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手背静脉穿刺机器人最优进针角度决策方法。

Decision Method of Optimal Needle Insertion Angle for Dorsal Hand Intravenous Robot.

机构信息

School of Information Science and Electrical Engineering, Shandong Jiaotong University, Jinan 250357, China.

Institute of Automation, Shandong Academy of Sciences, Jinan 250013, China.

出版信息

Sensors (Basel). 2023 Jan 11;23(2):848. doi: 10.3390/s23020848.

DOI:10.3390/s23020848
PMID:36679644
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9864605/
Abstract

In the context of COVID-19, the research on various aspects of the venipuncture robot field has become increasingly hot, but there has been little research on robotic needle insertion angles, primarily performed at a rough angle. This will increase the rate of puncture failure. Furthermore, there is sometimes significant pain due to the patients' differences. This paper investigates the optimal needle entry angle decision for a dorsal hand intravenous injection robot. The dorsal plane of the hand was obtained by a linear structured light scan, which was used as a basis for calculating the needle entry angle. Simulation experiments were also designed to determine the optimal needle entry angle. Firstly, the linear structured optical system was calibrated and optimized, and the error function was constructed and solved iteratively by the optimization method to eliminate measurement error. Besides, the dorsal hand was scanned to obtain the spatial point clouds of the needle entry area, and the least squares method was used to fit it to obtain the dorsal hand plane. Then, the needle entry angle was calculated based on the needle entry area plane. Finally, the changes in the penetration force under different needle entry angles were analyzed to determine the optimal needle insertion angle. According to the experimental results, the average error of the optimized structured light plane position was about 0.1 mm, which meets the needs of the project, and a large angle should be properly selected for needle insertion during the intravenous injection.

摘要

在 COVID-19 背景下,静脉穿刺机器人领域的各个方面的研究变得越来越热门,但对机器人进针角度的研究较少,主要以粗略角度进行,这会增加穿刺失败的概率。而且,由于患者的差异,有时会出现明显的疼痛。本文研究了一种手部背侧静脉注射机器人的最佳进针角度决策。通过线性结构光扫描获得手部背面平面,作为计算进针角度的基础。还设计了模拟实验来确定最佳进针角度。首先,对线性结构光系统进行标定和优化,构建误差函数,并通过优化方法进行迭代求解,以消除测量误差。此外,对手部背面进行扫描,获取进针区域的空间点云,并用最小二乘法拟合,得到手部背面平面。然后,根据进针区域平面计算进针角度。最后,分析不同进针角度下的穿透力变化,确定最佳进针角度。根据实验结果,优化后的结构光平面位置的平均误差约为 0.1mm,满足项目需求,静脉注射时应适当选择较大的进针角度。

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