用于微创手术的带微型力传感镊子的自动组织牵拉技术
Automatic Tissue Traction Using Miniature Force-Sensing Forceps for Minimally Invasive Surgery
AI总结：
针对机器人微创手术工具缺乏力传感控制的问题，基于自研微型力传感镊子提出含抓持、牵拉阶段的自动组织牵拉方法，通过力解耦实现多力控制，经离体实验验证可行，有望推动自主MIS发展。
摘要：
机器人微创手术（MIS）中自主组织操作的一个常见局限是工具层面缺乏力传感与控制。近期，本团队研发了可在组织操作过程中同时测量抓持力和拉力的微型力传感镊子。基于该设计，本文进一步提出一种自动组织牵拉方法，包含抓持和牵拉两个阶段。在此过程中，通过力解耦可分别或同时控制抓持力与拉力。力控制器建立在组织操作静态模型之上，考虑了力传感镊子与软组织之间的相互作用。通过一系列对比目标力、估计力和实际参考力的实验，验证了该力控制方法的有效性。为验证所提方法在手术应用中的可行性，本文采用双臂机器人系统在离体组织上开展了多种组织切除实验。最后，通过对比分析采用与未采用所提方法的各类离体组织切除实验，讨论了多力控制在组织牵拉中的优势，以及该方法在不同组织牵拉上的潜在泛化性。结果证实了采用具备多力控制的微型镊子实现自动组织牵拉的可行性，表明其有望推动自主微创手术的发展。展示实验的视频可在https://youtu.be/f5gXuXe67Ak查看。
英文摘要：
A common limitation of autonomous tissue manipulation in robotic minimally invasive surgery (MIS) is the absence of force sensing and control at the tool level. Recently, our team has developed miniature force-sensing forceps that can simultaneously measure the grasping and pulling forces during tissue manipulation. Based on this design, here we further present a method to automate tissue traction that comprises grasping and pulling stages. During this process, the grasping and pulling forces can be controlled either separately or simultaneously through force decoupling. The force controller is built upon a static model of tissue manipulation, considering the interaction between the force-sensing forceps and soft tissue. The efficacy of this force control approach is validated through a series of experiments comparing targeted, estimated, and actual reference forces. To verify the feasibility of the proposed method in surgical applications, various tissue resections are conducted on ex vivo tissues employing a dual-arm robotic setup. Finally, we discuss the benefits of multi-force control in tissue traction, evidenced through comparative analyses of various ex vivo tissue resections with and without the proposed method, and the potential generalization with traction on different tissues. The results affirm the feasibility of implementing automatic tissue traction using miniature forceps with multi-force control, suggesting its potential to promote autonomous MIS. A video demonstrating the experiments can be found at https://youtu.be/f5gXuXe67Ak.
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。
