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.

Up to now, there is no widely accepted quantitative evaluation scheme. Nowadays, an objective structured clinical examination has been proposed as a modern type of examination often used in medicine to test skills such as medical procedures, etc. The assessment of skills is realized by practical exams, in which students are evaluated by experienced examiner using a check list. However, the examiner lacks of information which cannot be obtained trough the simple observation of the task. Thanks to the advances in robot technology in embedded systems, etc.; more advanced evaluation tools can be conceived. For this reason, at Waseda University, we have proposed the development of a patient robot as an advanced evaluation tool to provide more detailed information of the task. As a first approach of our long-term research target, we have proposed the development of a suture/ligature training system which provides quantitative information of the movement of a dummy skin as well as information of the quality of task. In this paper; we describe the functionalities of the newest version, the Waseda-KyotoKagaku Skin No.2 Refined (WKS-2R), which has been designed to provide quantitative information of the task. In addition, we are proposing a new evaluation function which includes performance indexes and weighting coefficients. As a first approach, the weighting coefficients were determined by using the discriminant analysis. A set of experiments were proposed to confirm the effectiveness of the proposed evaluation function. From the preliminary results, the evaluation function was useful in detecting differences among different levels of expertise as well as detecting improvements during the training process by computing the learning curve.

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

Authors have proposed as a long-term goal, since 2004, the development of a patient robot which could serve for both training purposes as well as an evaluation tool of medical procedures. As a first approach, we have developed last year a suture and ligature training system named Waseda Kyotokagaku Suture No. 1 (WKS-1), which is composed by a commercial skin dummy with arrays of embedded sensors designed to acquire quantitative data of the task. The WKS-1 was designed to reproduce realistically the task conditions as well as providing objective assessment of the task performance. In particular, the proposed evaluation function considered the following performance indexes: time, displacement and force levels. By performing experiments with medical doctors and unskilled persons, we confirmed the effectiveness of WKS-1 to provide objective assessments of the task performance. However, the functionalities of WKS-1 were too restricted as few automatic procedures were implemented for the acquisition and processing of the collected data. Therefore; in this paper, we are presenting the Waseda Kyotokagaku Suture No. 2 (WKS-2). The WKS-2 has been designed to provide more detailed information of the task performance as well as improving its portability, connectivity, and usability. In addition, thanks to the design improvements on the WKS-2, we have proposed additional evaluation parameters to measure the quality of the suture (after the task has been completed). For this purpose, we proposed a image processing algorithm to automatically measure the width of sutures, the distance among them and the wound area. Preliminary experiments were carried out to verify its effectiveness.