Quantitative assessment of the surgical training methods with the suture/ligature training system WKS-2RII

  • Authors:
  • Jorge Solis;Nobuki Oshima;Hiroyuki Ishii;Noriyuki Matsuoka;Atsuo Takanishi;Kazuyuki Hatake

  • Affiliations:
  • Department of Modern Mechanical Engineering, Waseda University and Humanoid Robotics Institute, Waseda University;Department of Modern Mechanical Engineering, Waseda University, Tokyo, Japan;Consolidated Research Institute for Advanced Science and Medical Care, Waseda University, Tokyo, Japan;Kyotokagaku Co., Ltd., Kyoto, Japan;Department of Mechanical Engineering, Waseda University and Humanoid Robotics Institute, Waseda University;Kyotokagaku Co., Ltd., Kyoto, Japan

  • Venue:
  • ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
  • Year:
  • 2009

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Abstract

The emerging field of medical robotics is aiming in introducing intelligent tools to perform medical procedures. In particular, robotic researchers have been proposed advanced medical training systems to enhance motor dexterities of trainees. An efficient medical training system should be designed to simulate real-world conditions and to assure their effectiveness as the representation of the motor skills often differs among trainees. Up to now, several training simulators have been developed by medical companies designed to reproduce with high fidelity the human body. However, such devices are not designed to provide any information to trainees. Therefore, we have proposed the development of a Patient Robot which embeds sensors and actuators into a conventional human model. Due to its complexity, as a first approach; we are presenting the development of a suture training system designed to simulate the real-world task conditions as well as providing quantitative assessments. In particular; the Waseda-Kyotokagaku Suture No.2 Refined II is presented, which includes a new evaluation function to provide more detailed information of the task. A set of experiments were proposed to analyze the performance of trainees. From the experimental results, we could confirm its effectiveness to detect differences of the performance of trainees.