Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions

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.

A New Power Law Linking the Speed to the Geometry of Tool-Tip Orientation in Teleoperation of a Robot-Assisted Surgical System

“…18 surgical residents from the Soroka Medical Center participated in the experiment after signing an informed consent form approved by the Human Participants Research Committee of Ben-Gurion University of the Negev, Beer Sheva, Israel. The participants were seated in front of a surgeon's console of the dVRK [33] and used the Master Tool Manipulators (MTMs) to control two PSMs (Fig. 2a).…”

Using Artificial Intelligence for Assistance Systems to Bring Motor Learning Principles into Real World Motor Tasks

“…This could not only improve the training process of novices but could also develop a better understanding of motor learning principles applied in real world scenarios. In this context we already want to highlight that a prominent work in this direction is from the Nisky Lab, with a focus on surgical motor skills [ 231 , 291 , 292 , 293 ]. In the following, we will present an eight-step procedure that researchers can follow when applying the top-down approach ( Figure 9 ).…”

“…This is usually a complex motor skill performed in real world scenarios. Recent examples are a throwing task [ 237 ] or a surgical task [ 231 , 292 , 293 ]. In the throwing study [ 237 ], 20 nonexpert right-handed participants performed overarm throws, starting from a fixed initial position.…”

“…They argued that this platform would be beneficial since (1) both basic and complex tasks can be studied, (2) it can be extended to real world applications and (3) users with different levels of expertise exist for it. In a recent study [ 231 ], the performances of the participants was evaluated for a surgical needle driving task through artificial tissue under different haptic feedback conditions. They developed new metrics to evaluate the surgical needle driving task.…”

Accelerating Surgical Robotics Research: A Review of 10 Years With the da Vinci Research Kit

“…Haptic guidance and virtual fixtures (i.e., the application of forces to the trainee's manipulators to guide and teach the correct movement) have been of particular interest for augmenting the available information during training and in turn support more effective learning [221], [222], [234]. A recent systematic comparison of training augmentation in multiple sensorial domains was carried out using the dVRK [236].…”