Estimation of Degree of Interest in Comics Using a Stabilometer and an Acceleration Sensor

The current widespread usage of the Internet has made it possible to easily browse through various types of web content. However, owing to the large amount of available web content, it is difficult to recommend items that match the viewer’s preferences. Although existing recommendation systems can recommend content based on the viewer’s browsing history and previous purchases, there is still a lack of content relevance. Hence, a system is required that can quantitatively evaluate the viewer’s degree of interest by incorporating biometric information and thereby recommend the appropriate content. In previous studies, the viewer’s concentration was measured by employing an acceleration sensor on the back surface of a chair. However, the viewer’s posture cannot be estimated when the viewer does not lean against the backrest. Hence, in this study, we propose a method for estimating the degree of interest by employing a chair equipped with a body stabilometer on the seat and an acceleration sensor on the back. In this study, when the subject was leaning against the backrest, we determined the position of the center of gravity by employing a body stabilometer, and we acquired acceleration data by employing an acceleration sensor. Furthermore, we analyzed the movement vectors of the position of the center of gravity and the acceleration. Consequently, the vector angle was divided after every 15°, and the analysis was conducted by examining the vector magnitude in the angle. The obtained results indicate a positive correlation between the interest in each story and the vector magnitude. Therefore, it can be concluded that the degree of interest can be evaluated by incorporating the vector magnitude of the position of the center of gravity and the acceleration.