Cheng Zhuoqi, Dall'Alba Diego, Foti Simone, Mariani Andrea, Chupin Thibaud, Caldwell Darwin G, Ferrigno Giancarlo, De Momi Elena, Mattos Leonardo S, Fiorini Paolo
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy.
Altair Robotic Labs, Department of Computer Science, University of Verona, Verona, Italy.
Front Robot AI. 2019 Jul 17;6:55. doi: 10.3389/frobt.2019.00055. eCollection 2019.
The integration of intra-operative sensors into surgical robots is a hot research topic since this can significantly facilitate complex surgical procedures by enhancing surgical awareness with real-time tissue information. However, currently available intra-operative sensing technologies are mainly based on image processing and force feedback, which normally require heavy computation or complicated hardware modifications of existing surgical tools. This paper presents the design and integration of electrical bio-impedance sensing into a commercial surgical robot tool, leading to the creation of a novel smart instrument that allows the identification of tissues by simply touching them. In addition, an advanced user interface is designed to provide guidance during the use of the system and to allow augmented-reality visualization of the tissue identification results. The proposed system imposes minor hardware modifications to an existing surgical tool, but adds the capability to provide a wealth of data about the tissue being manipulated. This has great potential to allow the surgeon (or an autonomous robotic system) to better understand the surgical environment. To evaluate the system, a series of experiments were conducted. The experimental results demonstrate that the proposed sensing system can successfully identify different tissue types with 100% classification accuracy. In addition, the user interface was shown to effectively and intuitively guide the user to measure the electrical impedance of the target tissue, presenting the identification results as augmented-reality markers for simple and immediate recognition.
将术中传感器集成到手术机器人中是一个热门研究课题，因为这可以通过利用实时组织信息增强手术感知，显著促进复杂的外科手术。然而，目前可用的术中传感技术主要基于图像处理和力反馈，这通常需要大量计算或对现有手术工具进行复杂的硬件修改。本文介绍了将电阻抗传感设计并集成到商用手术机器人工具中，从而创造出一种新型智能器械，只需触摸就能识别组织。此外，还设计了一个先进的用户界面，在系统使用过程中提供指导，并允许对组织识别结果进行增强现实可视化。所提出的系统对现有手术工具进行的硬件修改较小，但增加了提供大量有关被操作组织数据的能力。这对于让外科医生（或自主机器人系统）更好地了解手术环境具有巨大潜力。为了评估该系统，进行了一系列实验。实验结果表明，所提出的传感系统能够以100%的分类准确率成功识别不同的组织类型。此外，用户界面被证明能够有效且直观地指导用户测量目标组织的电阻抗，并将识别结果呈现为增强现实标记以便简单直接识别。
