Development of a novel flow sensor to acquire quantitative information on BVM operation during airway management training

Abstract

Airway management is a basic skill for emergency rescue. The operation of the bag valve mask (BVM) is also a key process. The BVM is used not only to provide oxygen but also to detect if the tracheal tube is inserted in the trachea or bronchus. Currently, there are many training platforms designed for training medical staff. Most of them can provide subjective assessments. However, they are limited in providing quantitative assessments of a trainee's performance, including information about the BVM operation. Therefore, we propose a novel flow sensor system that can not only provide quantitative information on the trainee's BVM operation, but it can also objectively evaluate the trainee's performance. Waseda Kyotokagaku Airway — No.5 (WKA-5) is the newest platform that we designed for airway management training. It is based on robot technologies. Many types of sensors are embedded in this robot. In this paper, we will introduce the mechanical structure of the flow sensor and the method of data processing. The flow sensor has superior characteristics, such as high precision, quick responsiveness, and ease of maintenance. Using this sensor, we can analyze the frequency of BVM operation and detect whether the tracheal tube is in the proper position. Finally, several preliminary experiments have been carried out to confirm the accuracy and effectiveness of the flow sensor and evaluate the trainee's operation.