MP68-06 MOTION CAPTURE SYSTEM FOR OBJECTIVE ASSESSMENT OF TECHNICAL SKILLS DURING URETEROSCOPY

Abstract

You have accessJournal of UrologyCME1 Apr 2023MP68-06 MOTION CAPTURE SYSTEM FOR OBJECTIVE ASSESSMENT OF TECHNICAL SKILLS DURING URETEROSCOPY Brittany Berk, Mahdi Ebnali-Heidari, Christian Miccile, Roger Dias, and Daniel Wollin Brittany BerkBrittany Berk More articles by this author , Mahdi Ebnali-HeidariMahdi Ebnali-Heidari More articles by this author , Christian MiccileChristian Miccile More articles by this author , Roger DiasRoger Dias More articles by this author , and Daniel WollinDaniel Wollin More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003331.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Prior studies have demonstrated success with the use of motion analysis technology to assess surgical psychomotor skills. This study aims to provide preliminary evidence on the feasibility of using motion capture (mocap) system for objective assessment of a surgeon’s technical skills during ureteroscopic procedures. METHODS: Motion data of two participants, an attending urologist and a novice with no prior surgical training, were collected using the Rokoko smart suit with a sampling rate of 100 frames per second. This mocap system consists of 19 sensors; 9 Degree of Freedom (DoF) inertial measurement units each connected via wires to a hub for wireless communication (Figure 1). After data collection and preprocessing, data were analyzed to extract kinematic information from multiple joints including the wrist, elbow, and shoulder during a simulated ureteroscopic procedure. RESULTS: These data show that the distribution of x, y, and z locations of specific body part sensors can be visualized to investigate the variables associated with movement including speed, acceleration, the economy of movement, and smoothness. We found a distinct pattern in joint kinematics such as wrist, elbow flexion, extension, and pronation of the expert when compared to our novice participant. Interestingly, for most metrics, the expert showed a larger range of motion compared to the novice (Figure 1). To further investigate how these fluctuations are reflected in the frequency domains, we used Power Spectral Density (PSD) analysis, displaying the distribution of power of motion signals across distinct frequency bands. We found a higher power of motion in the signal associated with the expert left wrist flexion motion, indicating more energy spent on this motion pattern compared to the novice participant. CONCLUSIONS: In this study, we demonstrate that a mocap system is a feasible method for understanding surgeon motion patterns during ureteroscopic procedures. With additional participants and more complex simulated surgical tasks, we expect to utilize this framework to better delineate the ways that urologic surgeons utilize endoscopic equipment and to define metrics for the assessment of efficient kinematics related to surgical quality. This technology may also prove useful in urological surgical training in the future. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e954 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Brittany Berk More articles by this author Mahdi Ebnali-Heidari More articles by this author Christian Miccile More articles by this author Roger Dias More articles by this author Daniel Wollin More articles by this author Expand All Advertisement PDF downloadLoading ...