MP47-12 CORRELATING SIMULATOR AND LIVE ROBOTIC SURGICAL PERFORMANCE USING BIOMETRICS, SIMULATOR METRICS AND AUTOMATED PERFORMANCE METRICS

Abstract

You have accessJournal of UrologySurgical Technology & Simulation: Training & Skills Assessment II (MP47)1 Apr 2020MP47-12 CORRELATING SIMULATOR AND LIVE ROBOTIC SURGICAL PERFORMANCE USING BIOMETRICS, SIMULATOR METRICS AND AUTOMATED PERFORMANCE METRICS Andrew Cowan*, Runzhuo Ma, Jessica Nguyen, Swetha Rajkumar, Samuel Mingo, Ryan Hakim, Sandra Marshall, and Andrew Hung Andrew Cowan*Andrew Cowan* More articles by this author , Runzhuo MaRunzhuo Ma More articles by this author , Jessica NguyenJessica Nguyen More articles by this author , Swetha RajkumarSwetha Rajkumar More articles by this author , Samuel MingoSamuel Mingo More articles by this author , Ryan HakimRyan Hakim More articles by this author , Sandra MarshallSandra Marshall More articles by this author , and Andrew HungAndrew Hung More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000000902.012AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Multiple training modalities exist for robotic surgery, each with their own performance metrics. This study compares performance in analogous vesicourethral anastomosis (VUA) training tasks in simulation (SIM) and dry lab (DL). We investigated recorded biometrics, SIM metrics, and DL Automated Performance Metrics (APMs) to determine which were capable of distinguishing experts (E) from novices (N). METHODS: Experts (≥ 300 cases) and novices (<300 cases) performed VUAs during SIM and DL sessions (Figure 1). 22 SIM metrics (kinematics, safety) were captured by the simulator. 20 DL APMs (kinematics, events) were recorded by a systems data recorder (Intuitive Surgical). In both settings, task-evoked pupillary response (reported as Index of Cognitive Activity [ICA]) and heart rate variability (HRV) were collected as cognitive workload and stress biometrics respectively, analyzed by EyeWorks Cognitive Workload Software and Kubios HRV. Pearson Correlation, Mann-Whitney and Independent t-tests were used for the comparative analyses. RESULTS: Our study included 6 experts (median 1300 [400-3000]) and 11 novices (25 [0-250]). 7/8 metrics directly comparable between SIM and DL showed significant positive correlation (p≤0.032). Of these, kinematic metrics including path lengths of all three instruments (dominant/non-dominant hand, camera) (ρ≥0.677, p≤0.008), and both biometrics (ρ≥0.806, p≤0.001) showed strong correlations. ICA distinguished E v. N across SIM (p=0.036) and DL (p=0.024) while HRV was able in DL (p=0.024). 4/22 SIM metrics distinguished E v. N: task time (p=0.031), clutch usage (p=0.040), unnecessary needle piercings (p=0.026) and suspected injury to endopelvic fascia (p=0.040). This contrasts with 13/20 DL APMs (p≤0.038) including: linear velocities of all three instruments (p≤0.038) and dominant-hand instrument wrist articulation (p=0.013). Novices experienced higher cognitive workload in DL (p=0.024) and SIM (p=0.036), while all participants experienced higher cognitive workload in SIM than DL (p<0.001). CONCLUSIONS: A majority of performance metrics between SIM and DL exhibited a moderate to strong correlation. APMs on the live robot, focused on kinematics, are better able to distinguish E v. N surgical ability than error-focused SIM metrics. Source of Funding: This study was funded in part by an Intuitive Surgical Clinical Grant; Intuitive Surgical provided the systems data recorder. Research reported in this publication was supported in part by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number K23EB026493. © 2020 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 203Issue Supplement 4April 2020Page: e688-e689 Advertisement Copyright & Permissions© 2020 by American Urological Association Education and Research, Inc.MetricsAuthor Information Andrew Cowan* More articles by this author Runzhuo Ma More articles by this author Jessica Nguyen More articles by this author Swetha Rajkumar More articles by this author Samuel Mingo More articles by this author Ryan Hakim More articles by this author Sandra Marshall More articles by this author Andrew Hung More articles by this author Expand All Advertisement PDF downloadLoading ...