Abstract:The lack of haptic feedback in robotics-assisted surgery can result in tissue damage or accidental tool-tissue hits. This paper focuses on exploring the effect of haptic feedback via direct force reflection and visual presentation of force magnitudes on performance during suturing in robotics-assisted minimally invasive surgery (RAMIS). For this purpose, a haptics-enabled dual-arm master-slave teleoperation system capable of measuring tool-tissue interaction forces in all seven Degrees-of-Freedom (DOFs) was us… Show more
“…Results were inconclusive and were task dependent. We expected to find statistically significant differences between the three force feedback conditions, and more specifically, we expected to find worse performance at the end of teleoperation without force feedback compared to the other two force feedback conditions, as in Talasaz et al (2017), Currie et al (2017), and Gwilliam et al (2009), and applied forces in Okamura and Verner (2009) and Santos-Carreras et al (2010). Surprisingly, we did not see such differences for all the contrasts and metrics except one, consistently with task completion time in Verner and Okamura (2007), Santos-Carreras et al (2010), and task error in Okamura and Verner (2009).…”
Section: Discussionmentioning
confidence: 92%
“…Up to performing this research, several studies compared conditions with force feedback (usually one algorithm of force feedback) to no force feedback condition, and usually added another condition with the force feedback as visual information (Tholey et al, 2005;Arata et al, 2008;Gwilliam et al, 2009;Santos-Carreras et al, 2010;Talasaz et al, 2017). Results were inconclusive and were task dependent.…”
Section: Discussionmentioning
confidence: 99%
“…The benefit of haptic feedback to surgery is not yet fully understood (Okamura and Verner, 2009;Gibo et al, 2014;Yang et al, 2015;Talasaz et al, 2017). In a meta-analysis on the effect of force feedback, Weber and Schneider (2014) found that haptic feedback reduces the amount of force applied, but the reduction is smaller when depth perception is available.…”
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.
“…Results were inconclusive and were task dependent. We expected to find statistically significant differences between the three force feedback conditions, and more specifically, we expected to find worse performance at the end of teleoperation without force feedback compared to the other two force feedback conditions, as in Talasaz et al (2017), Currie et al (2017), and Gwilliam et al (2009), and applied forces in Okamura and Verner (2009) and Santos-Carreras et al (2010). Surprisingly, we did not see such differences for all the contrasts and metrics except one, consistently with task completion time in Verner and Okamura (2007), Santos-Carreras et al (2010), and task error in Okamura and Verner (2009).…”
Section: Discussionmentioning
confidence: 92%
“…Up to performing this research, several studies compared conditions with force feedback (usually one algorithm of force feedback) to no force feedback condition, and usually added another condition with the force feedback as visual information (Tholey et al, 2005;Arata et al, 2008;Gwilliam et al, 2009;Santos-Carreras et al, 2010;Talasaz et al, 2017). Results were inconclusive and were task dependent.…”
Section: Discussionmentioning
confidence: 99%
“…The benefit of haptic feedback to surgery is not yet fully understood (Okamura and Verner, 2009;Gibo et al, 2014;Yang et al, 2015;Talasaz et al, 2017). In a meta-analysis on the effect of force feedback, Weber and Schneider (2014) found that haptic feedback reduces the amount of force applied, but the reduction is smaller when depth perception is available.…”
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.
“…Hence, some future developments could also focus on reflecting the mechanical actions directly to the native dVRK masters, thus extending task space to bimanual procedures (yet renouncing to active feedback in grasping, since the related DoF is not active). However, for relevant tasks like knot tying, for which robotic surgeons struggle to detect the proper force intensity they are applying on the suture thread, the trade‐off between bimanual operation and active grasping seems not to be trivial. In parallel, more extensive investigations on grasping with enhanced master devices like the sigma.7 would permit to understand the potential benefits of force feedback over a wider range of tasks, including the aforementioned retraction maneuvers.…”
Section: Discussionmentioning
confidence: 99%
“…After several years during which the lack of haptic feedback was considered a limitation for the dV, 9 the mainstream opinion has become that robotic surgeons (necessarily trained on the dV) can compensate by using visual feedback, so that they do not suffer from that shortage. 10 On the other hand, many research studies claimed clear benefits from haptic feedback restoration for clinical applications/tasks requiring mechanical contrast perception for tissue discrimination (intraoperative palpation [11][12][13][14][15] ), precise tool-tissue interaction force rendering (incision/ dissection, 3,[16][17][18][19] catheter steering, 20 needle driving/suturing [21][22][23][24][25] ), or tissue/organ safe manipulation (tissue clutching, organ retraction 26,27 ).…”
Background
It was suggested that the lack of haptic feedback, formerly considered a limitation for the da Vinci robotic system, does not affect robotic surgeons because of training and compensation based on visual feedback. However, conclusive studies are still missing, and the interest in force reflection is rising again.
Methods
We integrated a seven‐DoF master into the da Vinci Research Kit. We designed tissue grasping, palpation, and incision tasks with robotic surgeons, to be performed by three groups of users (expert surgeons, medical residents, and nonsurgeons, five users/group), either with or without haptic feedback. Task‐specific quantitative metrics and a questionnaire were used for assessment.
Results
Force reflection made a statistically significant difference for both palpation (improved inclusion detection rate) and incision (decreased tissue damage).
Conclusions
Haptic feedback can improve key surgical outcomes for tasks requiring a pronounced cognitive burden for the surgeon, to be possibly negotiated with longer completion times.
Background: In robot‐assisted minimally invasive surgery, feedback as well as sensing of translational and grasping forces allows surgeons to manipulate the robots using an appropriate force. However, there have been limited reports on single instruments capable of sensing both forces (translational force and grasping force), with the exception of instruments with electronic sensors.Methods: In this study, a pneumatically driven surgical instrument capable of estimating both translational and grasping forces is developed. Our estimation method is based on the dynamics and pneumatic pressure changes of the instrument. For each force estimation, we applied a joint mechanism consisting of disks and a flexible backbone and constructed pneumatic driving systems, kinematic models, dynamic models, controller, and force estimator.Results: We confirmed experimentally that the mean absolute error between the measured forces and the estimated translational and grasping forces is 0.2 N or less for any condition. From these results, it is seen that the mechanical interference between the joint actuation mechanism and grasper actuation mechanism is negligibly small.Conclusions: A method for estimating both forces was proposed, and experimental results confirmed the effectiveness of the method.
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