Towards an Objective Tool for Evaluating the Surgical Skill

  • Giovanni Costantini
  • Giovanni Saggio
  • Laura Sbernini
  • Nicola Di Lorenzo
  • Daniele CasaliEmail author
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 620)


In this paper we present a system for the evaluation of the skill of a physician or physician student by means of the analysis of the movements of the hand. By comparing these movements to the ones of a set of subjects known to be skilled, we could tell if they are correct. We consider the execution of a typical surgical task: the suture. For the data acquisition we used the HiTEg sensory glove, then, we extract a set of features from data analysis and classify it by means of different kind of classifiers. We compared results from an RBF neural network and a Bayesian classifier. The system has been tested on a set of 18 subjects. We found that accuracy depends on the feature set that is used, and it can reach 94 % when we consider a set of 20 features: 9 of them are taken from data of bending sensor, 10 from accelerometers and gyroscopes, and one feature is the length of the gesture.


Neural networks Data glove Hand-gesture Classification Surgery 


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Giovanni Costantini
    • 1
  • Giovanni Saggio
    • 1
  • Laura Sbernini
    • 2
  • Nicola Di Lorenzo
    • 2
  • Daniele Casali
    • 1
    Email author
  1. 1.Departemet of Electronic a EngineeringUniversity of Rome “Tor Vergata”RomeItaly
  2. 2.Department of Experimental Medicine and SurgeryTor Vergata UniversityRomeItaly

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