Force Measurement in Robot-Assisted Endovascular Procedures: A Systematic Review

IF 4.3 Q2 ENGINEERING, BIOMEDICAL
Matteo Pantano;Teris Wolf;Philipp Mathea;Nikola Fischer;Steven J. Blacker;Christos Bergeles;Franziska Mathis-Ullrich;Thomas C. Booth;Sebastien Ourselin;Rebecca Fahrig
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Abstract

Use of endovascular therapy continues to expand due to its effectiveness and minimally invasive characteristics, prompting growing interest in teleoperated robotic systems that can extend access in rural settings and improve physicians well-being. These robotic platforms support physicians in the precise manipulation of endovascular devices, yet the importance for providing haptic feedback within such systems remains a topic of debate. Although several recent works outline techniques for delivering force cues to physicians, comparatively little attention has been given to how these forces are sensed on the robotic side. To clarify this aspect, this study reports a systematic literature review conducted under PRISMA guidelines, supplemented with a bias assessment to ensure cross-database consistency. From an initial pool of 641 publications, eight principal categories of endovascular forces were identified, with reported values spanning $0.17~{\mathrm {N }}$ to $2.61~{\mathrm {N }}$ and occasional peaks reaching $25~{\mathrm {N }}$ . Most measurements were obtained through sensors integrated either on the robotic drive mechanisms or directly onto endovascular devices. In addition, the review highlights emerging directions, including human limits on force sensing, hybrid sensing–estimation methods and the need for force characterization in therapeutic devices. Addressing these aspects will be essential to support future force feedback strategies and improve force assessments in both robot-assisted and manual endovascular procedures.
机器人辅助血管内手术的力测量:系统综述
由于其有效性和微创性,血管内治疗的应用不断扩大,促使人们对远程操作机器人系统的兴趣日益浓厚,这种系统可以扩大农村地区的使用范围,提高医生的福祉。这些机器人平台支持医生精确操作血管内装置,然而在这些系统中提供触觉反馈的重要性仍然是一个有争议的话题。尽管最近有几篇文章概述了向医生传递力信号的技术,但相对而言,很少有人关注机器人如何感知这些力。为了澄清这一点,本研究报告了在PRISMA指南下进行的系统文献综述,并辅以偏倚评估以确保跨数据库一致性。从最初的641份出版物中,确定了8种主要的血管内力类别,报告值范围为0.17~{\ mathm {N}}$至2.61~{\ mathm {N}}$,偶尔峰值达到25~{\ mathm {N}}$。大多数测量是通过集成在机器人驱动机构上或直接安装在血管内装置上的传感器获得的。此外,该综述还强调了新兴方向,包括人类对力传感的限制,混合传感估计方法以及治疗设备中力表征的需求。解决这些问题对于支持未来的力反馈策略和改进机器人辅助和人工血管内手术的力评估至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.80
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0.00%
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