Robot-assisted minimally invasive neurosurgical procedures: First experimental experience

1997 ◽  
pp. 319-322 ◽  
Author(s):  
Tushar M. Goradia ◽  
Russell H. Taylor ◽  
L. M. Auer
Keyword(s):  
Minimally Invasive ◽  
Neurosurgical Procedures ◽  
Robot Assisted

Robot-Assisted Off-Pump Minimally Invasive Reoperative Coronary Artery Bypass Grafting: Case Report

2004 ◽  
Vol 7 (6) ◽  
pp. E533-E534 ◽  
Author(s):  
Timothy P. Martens ◽  
Marco M. Hefti ◽  
Robert Kalimi ◽  
Craig R. Smith ◽  
Michael Argenziano
Keyword(s):  
Case Report ◽  
Coronary Artery ◽  
Coronary Artery Bypass Grafting ◽  
Minimally Invasive ◽  
Coronary Artery Bypass ◽  
Artery Bypass ◽  
Bypass Grafting ◽  
Robot Assisted ◽  
Artery Bypass Grafting ◽  
Off Pump

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

scholarly journals Incorporating model predictive control with fuzzy approximation for robot manipulation under remote center of motion constraint

2021 ◽  
Author(s):  
Hang Su ◽  
Junhao Zhang ◽  
Ziyu She ◽  
Xin Zhang ◽  
Ke Fan ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Robot Manipulator ◽  
Robot Assisted ◽  
External Disturbances ◽  
Fuzzy Approximation ◽  
Control Framework ◽  
Motion Constraint

AbstractRemote center of motion (RCM) constraint has attracted many research interests as one of the key challenges for robot-assisted minimally invasive surgery (RAMIS). Although it has been addressed by many studies, few of them treated the motion constraint with an independent workspace solution, which means they rely on the kinematics of the robot manipulator. This makes it difficult to replicate the solutions on other manipulators, which limits their population. In this paper, we propose a novel control framework by incorporating model predictive control (MPC) with the fuzzy approximation to improve the accuracy under the motion constraint. The fuzzy approximation is introduced to manage the kinematic uncertainties existing in the MPC control. Finally, simulations were performed and analyzed to validate the proposed algorithm. By comparison, the results prove that the proposed algorithm achieved success and satisfying performance in the presence of external disturbances.

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

Master Manipulator Optimization for Robot Assisted Minimally Invasive Surgery

2020 ◽  
Author(s):  
Mei Feng ◽  
Zhi Xue Ni ◽  
Ang Li ◽  
Lu Xiuquan ◽  
Yi Li Fu
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Robot Assisted

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.

scholarly journals Preliminary Results of Robotic Lobectomy in Stage IIIA-N2 NSCLC after Induction Treatment: A Case Control Study

2021 ◽  
Vol 10 (16) ◽  
pp. 3465
Author(s):  
Monica Casiraghi ◽  
Francesco Petrella ◽  
Giulia Sedda ◽  
Antonio Mazzella ◽  
Juliana Guarize ◽  
...  
Keyword(s):  
Lymph Node ◽  
Minimally Invasive ◽  
Open Surgery ◽  
Case Control Study ◽  
Locally Advanced ◽  
Case Control ◽  
Induction Treatment ◽  
Stage Iiia ◽  
Robot Assisted ◽  
Control Study

Despite there already being many studies on robotic surgery as a minimally invasive approach for non-small-cell lung cancer (NSCLC) patients, the use of this technique for stage III disease is still poorly described. These are the preliminary results of our prospective study on the safety and effectiveness of robotic approaches in patients with locally advanced NSCLC in terms of postoperative complications and oncological outcomes. Since 2016, we prospectively investigated 19 consecutive patients with NSCLC stage IIIA-pN2 (diagnosed by EBUS-TBNA) who underwent lobectomy and radical lymph node dissection with robotic approaches after induction treatment. Furthermore, we matched a case-control study with 46 patients treated with open surgery during the same period of time, with similar age, comorbidities, clinical stage and tumor size. The individual matched population was composed of 16 robot-assisted thoracic surgeries and 16 patients who underwent open surgery. The median time range of resection was inferior in the open group compared to robotic lobectomy (243 vs. 161 min; p < 0.001). Lymph node resection and positivity were not significantly different (p = 0.96 and p = 0.57, respectively). Moreover, no difference was observed for PFS (p = 0.16) or OS (p = 0.41). In conclusion, we demonstrated that the early outcomes and oncological results of N2-patients after robotic lobectomy were similar to those who had open surgery. Considering the advantages of minimally invasive surgery, robot-assisted lobectomy appears to be a safe approach to patients with locally advanced diseases.

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