A technical challenge for robot-assisted minimally invasive surgery: precision surgery on soft tissue

2005 ◽  
Vol 1 (2) ◽  
pp. 48-52 ◽  
Author(s):  
J Stallkamp ◽  
R D Schraft
Keyword(s):  
Minimally Invasive Surgery ◽  
Soft Tissue ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Robot Assisted ◽  
Technical Challenge

scholarly journals Toward Teaching by Demonstration for Robot-Assisted Minimally Invasive Surgery

2021 ◽  
pp. 1-11
Author(s):  
Hang Su ◽  
Andrea Mariani ◽  
Salih Ertug Ovur ◽  
Arianna Menciassi ◽  
Giancarlo Ferrigno ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Robot Assisted ◽  
Teaching By Demonstration

An electrical bioimpedance scanning system for subsurface tissue detection in Robot Assisted Minimally Invasive Surgery

2021 ◽  
pp. 1-1
Author(s):  
Zhuoqi Cheng ◽  
Kim Lindberg Schwaner ◽  
Diego Dall'Alba ◽  
Paolo Fiorini ◽  
Thiusius Rajeeth Savarimuthu
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Scanning System ◽  
Robot Assisted ◽  
Electrical Bioimpedance

Multimodal data fusion framework enhanced robot-assisted minimally invasive surgery

2021 ◽  
pp. 014233122098435
Author(s):  
Wen Qi ◽  
Hang Su ◽  
Ke Fan ◽  
Ziyang Chen ◽  
Jiehao Li ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Data Fusion ◽  
Invasive Surgery ◽  
Robot Control ◽  
Surgical Robot ◽  
Robot Assisted ◽  
Multimodal Data ◽  
Multimodal Data Fusion ◽  
Fusion Framework

The generous application of robot-assisted minimally invasive surgery (RAMIS) promotes human-machine interaction (HMI). Identifying various behaviors of doctors can enhance the RAMIS procedure for the redundant robot. It bridges intelligent robot control and activity recognition strategies in the operating room, including hand gestures and human activities. In this paper, to enhance identification in a dynamic situation, we propose a multimodal data fusion framework to provide multiple information for accuracy enhancement. Firstly, a multi-sensors based hardware structure is designed to capture varied data from various devices, including depth camera and smartphone. Furthermore, in different surgical tasks, the robot control mechanism can shift automatically. The experimental results evaluate the efficiency of developing the multimodal framework for RAMIS by comparing it with a single sensor system. Implementing the KUKA LWR4+ in a surgical robot environment indicates that the surgical robot systems can work with medical staff in the future.

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