Abstract

Robotic assisted minimally invasive surgery (RAMIS) systems present many advantages to the surgeon and patient over open and standard laparoscopic surgery. However, haptic feedback, which is crucial for the success of many surgical procedures, is still an open challenge in RAMIS. Understanding the way that haptic feedback affects performance and learning can be useful in the development of haptic feedback algorithms and teleoperation control systems. In this study, we examined the performance and learning of inexperienced participants under different haptic feedback conditions in a task of surgical needle driving via a soft homogeneous deformable object—an artificial tissue. We designed an experimental setup to characterize their movement trajectories and the forces that they applied on the artificial tissue. Participants first performed the task in an open condition, with a standard surgical needle holder, followed by teleoperation in one of three feedback conditions: (1) no haptic feedback, (2) haptic feedback based on position exchange, and (3) haptic feedback based on direct recording from a force sensor, and then again with the open needle holder. To quantify the effect of different force feedback conditions on the quality of needle driving, we developed novel metrics that assess the kinematics of needle driving and the tissue interaction forces, and we combined our novel metrics with classical metrics. We analyzed the final teleoperated performance in each condition, the improvement during teleoperation, and the aftereffect of teleoperation on the performance when using the open needle driver. We found that there is no significant difference in the final performance and in the aftereffect between the 3 conditions. Only the two conditions with force feedback presented statistically significant improvement during teleoperation in several of the metrics, but when we compared directly between the improvements in the three different feedback conditions none of the effects reached statistical significance. We discuss possible explanations for the relative similarity in performance. We conclude that we developed several new metrics for the quality of surgical needle driving, but even with these detailed metrics, the advantage of state of the art force feedback methods to tasks that require interaction with homogeneous soft tissue is questionable.

Highlights

  • Robot Assisted Minimally Invasive Surgery (RAMIS) refers to minimally invasive surgical procedure aided by robots

  • We compared the trajectories in the different da-Vinci Research Kit (dVRK) teleoperation conditions and the trajectories in the open needle driving

  • We grouped the metrics into the following categories: task performance, tissue interaction forces, kinematics, and motor control grounded metrics

Read more

Summary

Introduction

Robot Assisted Minimally Invasive Surgery (RAMIS) refers to minimally invasive surgical procedure aided by robots. In RAMIS, the surgeons use a robotic manipulator to operate robotic instruments inside the patient’s body. The surgical instrument (or end effector, e.g. gripper, scissors) follows the movement of the surgeon’s hands, usually with different motion scaling, filtering, and other possible manipulations or restrictions. Compared to minimally invasive surgery, RAMIS has several advantages, including 7 degrees-of-freedom (DOF), 3D high definition visual system, higher precision and accuracy, and more intuitive operation (e.g., preventing the Fulcrum effect). In 2017, the number of surgical procedures using the widespread da-Vinci RAMIS system was ∼877, 000 (Inc., 2017), and this number has been consistently growing over the years (Freschi et al, 2013; Enayati et al, 2016; Peters et al, 2018)

Objectives
Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call