Implicit Engagement Detection for Interactive Museums Using Brain-Computer Interfaces

Abstract

A rich museum experience is one that is engaging, educating and enjoyable to the visitors, such experiences can only be achieved by personalizing and enriching the museum experience according to the visitor's state. Neural signals from the brain can provide information about the affective and cognitive state of the person implicitly. With the rise of commercial Brain-Computer Interface devices, this technology can be utilized in extracting information to adapt various experiences to the state of the person. We propose a concept and preliminary study which uses brain signals from commercial grade Brain-Computer Interface (BCI) devices to implicitly detect museum visitors' engagement in the exhibited objects. Our concept and output of the study envision an experience where real time feedback based on visitors engagement is provided and the whole museum experience is tailored to each visitor's taste. In future work, we aim to gain external validity by testing our prototype in a museum setting.