用于经皮肾镜取石术的增强现实与人机协作框架：系统设计、实现与性能指标
Augmented Reality and Human-Robot Collaboration Framework for Percutaneous Nephrolithotomy: System Design, Implementation, and Performance Metrics
AI总结：
针对经皮肾镜取石术人工穿刺精度低、可重复性差的问题，研究提出结合OST-HMD增强现实可视化与人机协作的框架，通过多步配准和笛卡尔阻抗控制器实现引导，实验验证其精度更高、用户工作负荷更低，具备临床应用潜力。
摘要：
在经皮肾镜取石术（PCNL）过程中，外科医生需要在患者背部确定切口位置，将针头对准预先规划的路径，随后执行穿刺操作。目前该手术依靠超声或荧光透视成像引导针头方向，由人工完成，但存在精度有限、可重复性低的问题。本研究将基于光学透视头戴式显示器（OST-HMD）的增强现实（AR）可视化技术与人机协作（HRC）框架相结合，以提升外科医生的任务完成表现。具体而言，通过执行眼在手外标定、系统配准与全息模型配准实现视觉引导，并采用笛卡尔阻抗控制器在针头穿刺任务执行过程中引导操作者。研究开展了实验，将系统性能与传统人工穿刺流程、基于2D显示器的可视化界面进行对比。结果表明，所提出的框架在所有实验组中分别实现了最低的中位误差和标准差误差。此外，NASA-TLX用户评估结果显示，与其他实验设置相比，该框架完成任务所需的工作负荷评分最低。该框架能够增强外科医生的感知能力，助力无碰撞针头插入路径规划，并最大程度降低任务完成误差，在PCNL手术的临床应用中展现出巨大潜力。
英文摘要：
During Percutaneous Nephrolithotomy (PCNL) operations, the surgeon is required to define the incision point on the patient's back, align the needle to a pre-planned path, and perform puncture operations afterward. The procedure is currently performed manually using ultrasound or fluoroscopy imaging for needle orientation, which, however, implies limited accuracy and low reproducibility. This work incorporates Augmented Reality (AR) visualization with an optical see-through head-mounted display (OST-HMD) and Human-Robot Collaboration (HRC) framework to empower the surgeon's task completion performance. In detail, Eye-to-Hand calibration, system registration, and hologram model registration are performed to realize visual guidance. A Cartesian impedance controller is used to guide the operator during the needle puncture task execution. Experiments are conducted to verify the system performance compared with conventional manual puncture procedures and a 2D monitor-based visualisation interface. The results showed that the proposed framework achieves the lowest median and standard deviation error across all the experimental groups, respectively. Furthermore, the NASA-TLX user evaluation results indicate that the proposed framework requires the lowest workload score for task completion compared to other experimental setups. The proposed framework exhibits significant potential for clinical application in the PCNL task, as it enhances the surgeon's perception capability, facilitates collision-free needle insertion path planning, and minimises errors in task completion.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
