Augmented Reality and Robotic-Assistance for Percutaneous Nephrolithotomy

被引:14
|
作者
Ferraguti, Federica [1 ]
Minelli, Marco [1 ]
Farsoni, Saverio [2 ]
Bazzani, Stefano [1 ]
Bonfe, Marcello [2 ]
Vandanjon, Alexandre [3 ]
Puliatti, Stefano [4 ]
Bianchi, Giampaolo [4 ]
Secchi, Cristian [1 ]
机构
[1] Univ Modena & Reggio Emilia, Dipartimento Sci & Metodi Ingn, I-41121 Modena, Italy
[2] Univ Ferrara, Dipartimento Ingn, Ferrara, Italy
[3] Icam Inst Catholique Arts & Metiers, F-77127 Lieusaint, France
[4] Univ Modena & Reggio Emilia, Dipartimento Chirurg Med Odontoiatr & Sci Morfol, I-41121 Modena, Italy
来源
IEEE ROBOTICS AND AUTOMATION LETTERS | 2020年 / 5卷 / 03期
关键词
Surgical robotics; laparoscopy; medical robots and systems; human performance augmentation; KIDNEY; ACCESS; SIMULATION; TRENDS;
D O I
10.1109/LRA.2020.3002216
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Percutaneous nephrolithotomy (PCNL) is considered the gold standard for the treatment of patients with renal stones larger than 20 mm in diameter. The success and treatment outcomes of the surgery are very well known to be highly dependent on the precision and accuracy of the puncture step, since it must allow to reach the stone with a precise and direct path. Thus, performing the renal access during PCNL is the most crucial and challenging step of the procedure with the steepest learning curve. In this letter, we propose an innovative solution, based on an AR application combined with a robotic system, that can assist both an expert surgeon in improving the performance of the surgical operation and a novel surgeon in strongly reducing his/her learning curve. The proposed system is validated on a setup including a KUKA LWR 4+ robot and the Microsoft HoloLens as augmented reality headset, through experiments performed by a sample of 11 users.
引用
收藏
页码:4556 / 4563
页数:8
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