The rising popularity of learning techniques in data analysis has recently led to an increased need of large-scale datasets. In this study, we propose a system consisting of a VR game and a software platform designed to collect the player’s multimodal data, synchronized with the VR content, with the aim of creating a dataset for emotion detection and recognition. The game was implemented ad-hoc in order to elicit joy and frustration, following the emotion elicitation process described by Roseman’s appraisal theory. In this preliminary study, 5 participants played our VR game along with pre-existing ones and self-reported experienced emotions.