User Identification Method based on Head Shape Using Pressure Sensors Embedded in a Helmet

Abstract

Various types of helmets exist, including industrial protective helmets, motorcycle helmets, sports helmets, and military/police helmets. By identifying individuals wearing a helmet, their name, affiliation, and qualification can be presented on a display mounted on the helmet, and sensor data collected through the helmet, such as acceleration, video, and eye-tracking data, can be labeled with the user's ID. In this paper, we propose a user identification method based on head shape using a helmet equipped with 32 pressure sensors. Our method has two functions: user identification and authentication. User identification is based on the assumption that a single helmet is shared by multiple individuals. The goal of this method is to identify which of the registered people is the person wearing the helmet. User authentication determines whether the individual wearing the helmet is the individual with the ID when the ID is provided to the system. In the evaluation, we obtained sensor values for 2 seconds 20 times from nine subjects as head shape data. The accuracy was evaluated using 5-fold cross-validation, and we achieved 100% accuracy with five sensors and 92% with two sensors for user identification and an average equal error rate of 0.076 with 32 sensors for user authentication.