Development of a Suture/Ligature training system designed to provide quantitative information of the learning progress of trainees

Nobuki Oshima*, Muhamad Aizudding, Ryu Midorikawa, Jorge Solis, Yu Ogura, Atsuo Takanishi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Citations (Scopus)

Abstract

Surgeons, during a medical intervention, perform different kinds of manual tasks with dexterity and precision. In order to assure the success of the intervention, medical students are trained several years using training models so that they can perform such tasks with accuracy to avoid any possible risk to patients. However, current training models are merely designed to imitate the surgical procedure without providing any further information about the how well the task was done. For that reason; in this paper, the development of a Suture/Ligature Training System is proposed to imitate surgical procedures as well as provide quantitative information of the learning progress of trainees. As a first approach, a training system was designed to simulate the suture and ligature tasks. The proposed training system includes a skin dummy with an array of embedded photo interrupters to detect the movement of the skin dummy; without requiring any modification on the surgical instrument. In this paper, different task parameters were proposed to understand trainees' learning progress and different experiments were carried out to identify the evaluation parameters that may provide useful information about how well the task was performed. As a result from the experiments, the evaluation parameters for the suture and ligature were determined. Finally, an evaluation function was proposed and further experiments were proposed to verify its effectiveness. From the results of the experiments, we could effectively distinguish quantitatively the differences of skill levels between surgeons and unskilled persons as well as identifying the learning progress of trainees by plotting the learning curve.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Robotics and Automation, ICRA'07
Pages2285-2291
Number of pages7
DOIs
Publication statusPublished - 2007 Nov 27
Event2007 IEEE International Conference on Robotics and Automation, ICRA'07 - Rome, Italy
Duration: 2007 Apr 102007 Apr 14

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2007 IEEE International Conference on Robotics and Automation, ICRA'07
Country/TerritoryItaly
CityRome
Period07/4/1007/4/14

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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