Żelechowski Marek, Faludi Balázs, Karnam Murali, Gerig Nicolas, Rauter Georg, Cattin Philippe C
Center for medical Image Analysis & Navigation (CIAN), Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
Bio-Inspired RObots for MEDicine-Laboratory (BIROMED-lab), Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
Int J Comput Assist Radiol Surg. 2023 Nov;18(11):1951-1959. doi: 10.1007/s11548-023-02967-2. Epub 2023 Jun 9.
Understanding the properties and aspects of the robotic system is essential to a successful medical intervention, as different capabilities and limits characterize each. Robot positioning is a crucial step in the surgical setup that ensures proper reachability to the desired port locations and facilitates docking procedures. This very demanding task requires much experience to master, especially with multiple trocars, increasing the barrier of entry for surgeons in training.
Previously, we demonstrated an Augmented Reality-based system to visualize the rotational workspace of the robotic system and proved it helps the surgical staff to optimize patient positioning for single-port interventions. In this work, we implemented a new algorithm to allow for an automatic, real-time robotic arm positioning for multiple ports.
Our system, based on the rotational workspace data of the robotic arm and the set of trocar locations, can calculate the optimal position of the robotic arm in milliseconds for the positional and in seconds for the rotational workspace in virtual and augmented reality setups.
Following the previous work, we extended our system to support multiple ports to cover a broader range of surgical procedures and introduced the automatic positioning component. Our solution can decrease the surgical setup time and eliminate the need to repositioning the robot mid-procedure and is suitable both for the preoperative planning step using VR and in the operating room-running on an AR headset.
了解机器人系统的特性和各个方面对于成功的医学干预至关重要,因为每个系统都有不同的能力和局限性。机器人定位是手术准备中的关键步骤,可确保能够顺利到达所需的端口位置并便于对接程序。这项要求极高的任务需要大量经验才能掌握,尤其是在使用多个套管针时,这增加了实习外科医生的准入门槛。
此前,我们展示了一个基于增强现实的系统,用于可视化机器人系统的旋转工作空间,并证明它有助于手术人员优化单端口干预的患者体位。在这项工作中,我们实现了一种新算法,以实现多端口机器人手臂的自动实时定位。
我们的系统基于机器人手臂的旋转工作空间数据和套管针位置集,在虚拟和增强现实设置中,能够在几毫秒内计算出机器人手臂的最佳位置,对于旋转工作空间则需要几秒。
继之前的工作之后,我们扩展了系统以支持多个端口,从而涵盖更广泛的外科手术程序,并引入了自动定位组件。我们的解决方案可以减少手术准备时间,消除术中重新定位机器人的需要,并且既适用于使用虚拟现实的术前规划步骤,也适用于在手术室中使用增强现实头戴设备进行操作。