Towards near real-time assessment of surgical skills: A comparison of feature extraction techniques.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 19, 2019

Abstract

BACKGROUND AND OBJECTIVE: Surgical skill assessment aims to objectively evaluate and provide constructive feedback for trainee surgeons. Conventional methods require direct observation with assessment from surgical experts which are both unscalable and subjective. The recent involvement of surgical robotic systems in the operating room has facilitated the ability of automated evaluation of the expertise level of trainees for certain representative maneuvers by using machine learning for motion analysis. The features extraction technique plays a critical role in such an automated surgical skill assessment system.

Authors

  • Nguyen Xuan Anh
    Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, Australia.
  • Ramesh Mark Nataraja
    Department of Surgical Simulation, Monash Children's Hospital, Melbourne, Australia; Department of Paediatrics, School of Clinical Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
  • Sunita Chauhan
    Department of Mechanical and Aerospace Engineering, Monash University, Clayton, Victoria, 3800, Australia. Electronic address: Sunita.Chauhan@monash.edu.

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