In corneal transplantation, 16 submillimeter-sized sutures are generated around the circular-shaped graft cornea. A major challenge in corneal transplantation is the generation of uniformly shaped sutures, where the suture shapes need to be changed depending on the patient. In this study, a corneal suturing robot that can produce sutures of the desired shape with high uniformity is described. The proposed robot manipulates the corneal tissue deformation before inserting the needle for suture shape control. A simulation using the finite element method was proposed to predict the suture shape. The suturing experiment was conducted on a porcine model, and the result was compared with the simulation. As a result, the proposed robot was able to generate sutures with a standard deviation of 108 $\mu$ m in length and 36 $\mu$ m in depth. The mean absolute error between the simulation and the experiment was 95 $\mu$ m in length and 31 $\mu$ m in depth. This is the first study to suggest a method for controlling the suture shape and quantitatively analyzing it in ophthalmic surgery.

中文翻译：

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能够为角膜移植手术生产所需形状缝线的角膜缝合机器人

在角膜移植中，在圆形移植角膜周围产生 16 条亚毫米大小的缝合线。角膜移植的一个主要挑战是产生均匀形状的缝线，其中缝线形状需要根据患者的不同而改变。在这项研究中，描述了一种角膜缝合机器人，它可以产生具有高均匀性的所需形状的缝合线。所提出的机器人在插入针头以控制缝合线形状之前操纵角膜组织变形。提出了使用有限元方法的模拟来预测缝合线形状。在猪模型上进行缝合实验，并将结果与​​模拟进行比较。结果，所提出的机器人能够生成标准偏差为 108 $\mu$ m 长度和 36 $\mu$ m 深度的缝线。模拟和实验之间的平均绝对误差为 95 $\mu$ m 长度和 31 $\mu$ m 深度。这是首次提出在眼科手术中控制缝合线形状并对其进行定量分析的方法的研究。