Qualitative and quantitative analysis of the learning curve of a simulated surgical task on the da Vinci system

  • J. D. Hernandez
  • S. D. Bann
  • Y. Munz
  • K. Moorthy
  • V. Datta
  • S. Martin
  • A. Dosis
  • F. Bello
  • A. Darzi
  • T. Rockall
Original article



Robotic telemanipulation systems provide solutions to the problems of less dexterity and visual constraints of minimally invasive surgery (MIS). However, their influence over surgeons’ dexterity and learning curve needs to be assessed. We present motion analysis as an objective method to measure performance and learning progress.


Thirteen surgeons completed five synthetic small bowel anastomoses using the da Vinci system. Objective Structured Assessment of Technical Skills (OSATS) allowed qualitative analysis. Quantitative analysis used API software of the system to retrieve real-time robotic signal data of time, path length, and number of movements. Wilcoxon signed ranks test was used for statistical analysis. A p value <0.05 was considered significant.


OSATS global scores were 18.6 points for the first attempt and 26 for the fifth attempt (p < 0.02, Cronbach’s alpha = 0.894). Paired data of motion analysis for attempts 1 vs 5 showed significant change: time taken 3507 sec and 2287 sec (p < 0.008), total number of movements 2411 and 1387 (p = 0.01), total path length 21,630 cm and 13,941 cm (p = 0.01).


A rapid learning curve to a competent level using the da Vinci system is possible aided by the system’s intuitive motion. Motion analysis is a useful tool to measure performance in the da Vinci system compared to OSATS and time alone.


Minimally invasive surgery Skills assessment Telemanipulator systems 


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Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • J. D. Hernandez
    • 1
  • S. D. Bann
    • 1
  • Y. Munz
    • 1
  • K. Moorthy
    • 1
  • V. Datta
    • 1
  • S. Martin
    • 1
  • A. Dosis
    • 1
  • F. Bello
    • 1
  • A. Darzi
    • 1
  • T. Rockall
    • 1
  1. 1.Department of Surgical Oncology and TechnologyImperial College School of Medicine, St. Mary’s HospitalLondon, W2 1 NYUnited Kingdom

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