Abstract

You have accessJournal of UrologyTechnology & Instruments: Surgical Education & Skills Assessment I1 Apr 2015MP22-11 UNDERSTANDING SURGICAL PERFORMANCE DURING ROBOT-ASSISTED SURGERY: PIERCING THE HORNET'S NEST Khurshid Guru, Somayeh Shafiei, Atif Khan, Mohamed Sharif, Syed Johar Raza, Thomas Fiorica, Mohammad M. Durrani, and Ehsan Esfahani Khurshid GuruKhurshid Guru More articles by this author , Somayeh ShafieiSomayeh Shafiei More articles by this author , Atif KhanAtif Khan More articles by this author , Mohamed SharifMohamed Sharif More articles by this author , Syed Johar RazaSyed Johar Raza More articles by this author , Thomas FioricaThomas Fiorica More articles by this author , Mohammad M. DurraniMohammad M. Durrani More articles by this author , and Ehsan EsfahaniEhsan Esfahani More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.1023AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Surgery is performed in a dynamic environment that constantly challenges human performance. We attempted to understand cognitive skills of an expert surgeon during robot-assisted surgery. METHODS In an IRB approved study performed during 2013–14, NASA TLX questionnaire with surgical field notes were simultaneously completed. A wireless EEG headset was used to monitor brain activity during all procedures. Three key portions evaluated: Lysis of adhesions (n=20), Extended Lymph Node Dissection (n=21) and Urethro-vesical Anastomosis (n=19). Cognitive metrics extracted were distraction, mental workload and mental state. RESULTS LOA: Mental state (EEG) positively correlated with performance (NASA TLX). Utilizing more mental resources resulted in better performance as self-reported (NASA TLX). Outcomes of LOA are highly depended on cognitive and decision making skills. ELND: Negative correlation between distraction level (EEG) and mental demand, physical demand and effort (NASA TLX). During less challenging ELND, surgeon's mental engagement was lower. Moreover, similar to LOA utilizing more mental resources resulted in better performance (NASA TLX). Combination of these observations indicates importance of cognitive and motor skills depending on the operative challenges. UVA: Workload (EEG) negatively correlated with mental demand, temporal demand and performance (NASA TLX). The EEG recorded workload as seen here is a combination of both cognitive (finding solution) and motor workload (execution). Since there is no significant correlation between any self-reported indices (NASA TLX) and mental state (EEG), majority of workload measured is contributed by motor workload of an expert surgeon. During UVA, muscle memory and motor skills of expert are keys to completing the UVA. CONCLUSIONS The first study which defines cognitive function during robot-assisted surgery. Different surgical steps demand varying skills to perform surgery with precision and safety. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e245-e246 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Khurshid Guru More articles by this author Somayeh Shafiei More articles by this author Atif Khan More articles by this author Mohamed Sharif More articles by this author Syed Johar Raza More articles by this author Thomas Fiorica More articles by this author Mohammad M. Durrani More articles by this author Ehsan Esfahani More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

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