Development of Patient Scenario Generation which can reproduce characteristics of the patient for simulating real-world conditions of task for airway management training system WKA-3

• Published in: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems pp. 331 - 336
• Main Authors: Noh, Y, Shimomura, A, Sato, K, Segawa, M, Ishii, H, Solis, J, Takanishi, A, Hatake, K
• Format: Conference Proceeding
• Language: English; Japanese
• Published: IEEE 01.10.2010
• Subjects: Force; Muscles; Sensor systems; Surgery; Tongue; Training
• DOI: 10.1109/IROS.2010.5648794
• ISBN: 9781424466740; 1424466741
• ISSN: 2153-0858

Recently, in medical field, different training methods for medical staff have been proposed. However, the lack of knowledge on the real improvements of trainees makes difficult the real effectiveness of those proposed methods. Therefore, we are proposing an Active Training system for the effective medical training. The Active training system is characterized by providing quantitative information of the trainee's performance of the task to the trainee, simulating real-world conditions of the task, and assuring training effectiveness. In order to fulfill each of these characteristics, we have developed Waseda Kyotokagaku Airway No.3 (WKA-3) which makes it possible to obtain quantitative information for the trainee's performance and reproduce the various cases, individual differences for the airway difficulties for the simulating real-world conditions of the task. In this paper, we are proposing a patient scenario generation which can reproduce the characteristics of the patient simulating real-world conditions of the task for WKA-3. In emergent situation or surgical operation, the characteristics of patients are presented in the three parameters such as: patient initial conditions, time variant status change, and reflex action. By adjusting, and combining each of the three parameters, we can reproduce the various patient scenarios. In this paper, we also state how to generate the Patient Scenario Generation using the position control and virtual compliance control. Finally, a set of experiments has been carried out to the doctor subjects in order to verify effectiveness of the proposed Patient Scenario Generation, and discuss the doctors about the result of the experiments.