Srikant Vallabhajosula, PhD, Irene Suh, MS, Mukul Mukherjee, PhD, Jung-Hung Chien, MS, Chun-Kai Huang, MS, Dmitry Oleynikov, MD FACS, Ka-Chun Siu, PhD PT. Nebraska Biomechanics Core Facility, University of Nebraska at Omaha, Omaha, NE, USA; Department of Surgery, College of Public Health, Center for Advanced Surgical Technology, University of Nebraska Medical Center, Omaha, NE, USA
INTRODUCTION: The growing prevalence of robotic laparoscopic surgery specially using the da Vinci Surgical System (dVSS) places a great demand for establishing standardized training and evaluation procedures. Further, this training can be made more effective by providing augmented feedback to the learner. Researchers have previously looked at the effect of such feedback on different kinds of surgical tasks. Our previous research showed the existence of feedback-specific effects where participants with speed feedback performed the tasks faster than other groups after training. However it is unknown how the effect of a specific type of feedback is affected by the type of task and how that effect is influenced by learning.
METHODS AND PROCEDURES: Twenty-two novice users (age: 25±5 years) of the dVSS participated in this study. Subjects performed and/or practiced 3 tasks using the dVSS throughout this study: bimanual carrying (BC), needle passing (NP), and suture tying (ST). Participants performed 21 trials of each task divided into 4 training blocks: 3 pre-training trials – PRE, 10 training trials with augmented visual feedback, 3 post-training trials – POST, and 5 retention trials – RET for each task. Pre-training, training, and POST trials were performed during first session. Retention trials were performed 2 weeks after the first session. Task order was randomized between subjects but was the same between training blocks. Subjects were randomly assigned to 1 of 4 feedback groups: speed (SP, n = 5), grip force (GRIP, n = 6), relative phase between left and right grasper movement (RP, n = 5), and video (VID, n = 6). Performance measures were time to task completion (TTC), total distance traveled (D), speed (S), curvature, relative phase and grip force (F). A 3 (tasks: BC, NP, ST) x 3 (conditions: PRE, POST, RET) repeated measures ANOVA was used for each visual feedback and for each dependent variable. The level of significance was set at 0.05.
RESULTS AND DISCUSSION: Significant interaction for TTC and curvature showed that the RP training improved temporal measures of more complicated tasks (ST) compared to basic tasks (BC). SP feedback training significantly improved the performance in simple tasks (BC) in terms of TTC, D, S, curvature and F even after retention along with lesser long-term effect on complicated tasks like ST. GRIP feedback training resulted in shorter TTC, lesser D, faster S, smaller curvature, lesser F during simple tasks (BC) with moderate improvements for intermediate tasks like NP. For the VID feedback training group, faster S, lesser curvature, lesser F for the BC task and the improvements in most of the outcome measures were evident only after 2 weeks retention. For all the types of feedback training, BC and NP tasks were performed with out-of-phase coordination while the ST task was performed with in-phase coordination.
CONCLUSION: Task specific augmented visual feedback is beneficial to robotic surgical training. Particularly, the RP feedback could be useful for training complex tasks. Future studies need to evaluate additional benefits of utilizing multiple types of feedback on a particular task.
Program Number: P493