A New Suture Needle State estimation Method Based on Electrical Impedance Sensing

K. Schwaner, Zhuoqi Cheng, T. Savarimuthu
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Abstract

Autonomous surgical task execution has the potential to improve surgeons’ working conditions, increase hos- pital throughput, and better patient outcomes in the future. While fully autonomous robotic minimally inva- sive surgery (RMIS) is currently unrealistic for several reasons, partly automated surgery – or task autonomy [1] – is being explored for different surgical tasks. One such task is suturing, which involves complex motions in a challenging environment. Automating the suturing task using surgical robots has been attracting research interest (see, e.g., [2]–[4] for recent studies). Despite these advances, automated suturing is still lim- ited to controlled environments and is not yet applicable in realistic surgical settings. This paper presents a step towards autonomous robotic suturing. Specifically, we propose a method for suture needle state estimation during insertion into soft tissue based on electrical bioimpedance (EBI) sensing. EBI is an advantageous sensing modality in RMIS, given that it is non-invasive and requires only minor modifications to existing surgical instruments. In this study, we equip a surgical robot with EBI sensing capabilities, allowing the robot to measure the electrical impedance between a needle driver instrument and a common ground elec- trode. The proposed method requires a suture needle with insulation coating except for its tip, end, and notch in the middle. We conducted an experiment for concept validation based on ex vivo animal tissue where we obtained a 98.8 % prediction accuracy on four different suture needle insertion states. Most interestingly, we could accurately determine when the needle tip exits after being pushed through soft tissue, which is chal- lenging to do with, e.g., computer vision due to the needle’s small size and occlusions. The needle tip exiting is valuable information as often one wishes to grasp the needle tip with a second manipulator to complete the suture throw by pulling the needle through the tissue.
一种基于电阻抗传感的缝线针状态估计新方法
自主手术任务执行有可能改善外科医生的工作条件,增加医院吞吐量,并在未来改善患者的治疗效果。由于一些原因,完全自主的机器人微创手术(RMIS)目前是不现实的,部分自动化手术-或任务自主性[1]-正在探索不同的手术任务。其中一项任务是缝合,这需要在具有挑战性的环境中进行复杂的动作。使用手术机器人自动化缝合任务已经引起了人们的研究兴趣(参见最近的研究,例如[2]-[4])。尽管取得了这些进步,但自动缝合仍然局限于受控环境,尚未适用于实际的手术环境。本文介绍了迈向自主机器人缝合的一步。具体来说,我们提出了一种基于电生物阻抗(EBI)传感的缝合针插入软组织时状态估计方法。EBI是非侵入性的,只需要对现有的手术器械进行微小的修改,是RMIS中一种有利的传感方式。在这项研究中,我们为手术机器人配备了EBI传感功能,使机器人能够测量针头驱动器和公共接地电极之间的电阻抗。所提出的方法要求缝合针除针尖、端部和中间缺口外具有绝缘涂层。我们进行了基于离体动物组织的概念验证实验,在四种不同的缝线针插入状态下,我们获得了98.8%的预测准确率。最有趣的是,我们可以准确地确定针尖在被推动穿过软组织后何时退出,这是具有挑战性的,例如,由于针头的小尺寸和闭塞性,计算机视觉很难做到。针尖的退出是有价值的信息,因为通常人们希望用第二个操作器抓住针尖,通过将针穿过组织来完成缝合。
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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