Patel Niravkumar, Urias Muller, Ebrahimi Ali, Taylor Russell H, Gehlbach Peter, Iordachita Iulian
Laboratory for Computational Sensing and Robotics, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD USA-21218.
Indian Institute of Technology Madras, Chennai, India.
IEEE Trans Med Robot Bionics. 2022 Aug;4(3):578-587. doi: 10.1109/tmrb.2022.3191441. Epub 2022 Jul 15.
In recent years, robotic assistance in vitreoretinal surgery has moved from a benchtop environment to the operating rooms. Emerging robotic systems improve tool manoeuvrability and provide precise tool motions in a constrained intraocular environment and reduce/remove hand tremor. However, often due to their stiff and bulky mechanical structure, they diminish the perception of tool-to-sclera (scleral) forces, on which the surgeon relies, for eyeball manipulation. In this paper we measure these scleral forces and actively control the robot to keep them under a predefined threshold. Scleral forces are measured using a Fiber Bragg Grating (FBG) based force sensing instrument in an rabbit eye model in manual, cooperative robotic assistance with no scleral force control (NC), adaptive scleral force norm control (ANC) and adaptive scleral force component control (ACC) methods. To the best of our knowledge, this is the first time that the scleral forces are measured in an eye model during robot assisted vitreoretinal procedures. An experienced retinal surgeon repeated an intraocular tool manipulation (ITM) task 10 times in four rabbit eyes and a phantom eyeball, for a total of 50 repetitions in each control mode. Statistical analysis shows that the ANC and ACC control schemes restrict the duration of the undesired scleral forces to 4.41% and 14.53% as compared to 43.30% and 35.28% in manual and NC cases, respectively during the studies. These results show that the active robot control schemes can maintain applied scleral forces below a desired threshold during robot-assisted vitreoretinal surgery. The scleral forces measurements in this study may enable a better understanding of tool-to-sclera interactions during vitreoretinal surgery and the proposed control strategies could be extended to other microsurgery and robot-assisted interventions.
近年来，玻璃体视网膜手术中的机器人辅助已从实验室环境进入手术室。新兴的机器人系统提高了工具的可操作性，并在受限的眼内环境中提供精确的工具运动，减少/消除了手部震颤。然而，由于其机械结构僵硬且笨重，它们削弱了外科医生在眼球操作时所依赖的工具与巩膜（眼球外层的坚韧纤维膜）之间的力的感知。在本文中，我们测量了这些巩膜力，并主动控制机器人使其保持在预定义的阈值以下。在兔眼模型中，使用基于光纤布拉格光栅（FBG）的力传感仪器，通过手动操作、无巩膜力控制（NC）的协作机器人辅助、自适应巩膜力规范控制（ANC）和自适应巩膜力分量控制（ACC）方法来测量巩膜力。据我们所知，这是首次在机器人辅助玻璃体视网膜手术过程中在眼模型中测量巩膜力。一位经验丰富的视网膜外科医生在四只兔眼和一个眼球模型中重复进行眼内工具操作（ITM）任务10次，每种控制模式下共重复50次。统计分析表明，在研究过程中，与手动操作和NC情况分别为43.30%和35.28%相比，ANC和ACC控制方案将不期望的巩膜力持续时间限制在4.41%和14.53%。这些结果表明，主动机器人控制方案可以在机器人辅助玻璃体视网膜手术期间将施加的巩膜力维持在期望阈值以下。本研究中的巩膜力测量可能有助于更好地理解玻璃体视网膜手术期间工具与巩膜之间的相互作用，并且所提出的控制策略可以扩展到其他显微手术和机器人辅助干预中。
