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Waseda
1.Objective |
1.Objective
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, since 2005, we have been developing the Evaluation System for Surgical Skill which is proposed to imitate surgical procedures as well as provide quantitative information of the learning progress of trainees.
In addition, this system is developed with Kyoto-Kagaku co., Ltd and planning to sell this system in near future.
2.Overview
In 2008, we developed the Evaluation system for surgical skill WKS-2RII(Waseda Kyotokagaku Skin No.2 Refined II) which is composed by a dummy skin with embedded sensors, a webcam and a personal computer.
The main modifications from WKS-2R are software and evaluation parameters.
In order to perform the training session, an user-friendly GUI was developed. Meanwhile the trainee is performing the task, the information about the movement of thedummy skin is recorded by using a Peripheral interface controller. In addition, to perform the image processing of the suture The collected information is then managed by means of a database.
Thanks to the improvements in both hardware and software, now we are able of performing more detailed field experiments.
We have proposed evaluation parameters which are considered on theOSCEexamination’s checklist.
From our discussion with medical doctors, we believe this new evaluation function evaluates the suture skill comprehensively.
We proposed a new evaluation function, which it is shown in Eq. 1.
By using Eq. 1, the suture/ligature task can be evaluated by means of aunique evaluation function which includes information obtained from both embedded sensors and image suture processing. ．
Evaluation parameters are following 6 parameters
-Time，Force in Tissue，Judging Tension，Equidistance，Distance between Sutures，Wound Dehiscence-.
In order to determine the optimal values of the weight coefficients, more advanced approaches can be used, such as: Discriminant Analysis
As a result, the following values were considered for the weight coefficients．
