In Affective Computing research field, different tools and devices are used to acquire physiological data and users' emotional state. Video games, as entertainment software, are developed considering which types of emotions have to be experienced by the players. Unfortunately, the researches on the connection between video games and emotions usually do not provide a quantitative outcome about the emotional impact of different game features. This essay has the main goal to provide an overview on a set of tools that can be used to design an experimental setup aimed to acquire physiological data and players' mental state, using Affective Computing methodology, in video game research. In particular, we propose a hardware architecture to collect physiological data, a software to store, visualize, and synchronize the acquired data (DAPIS), and a tool able to self-assess the users' emotions (ESAT). The overall architecture also involves a method to define game events. The considered physiological data are: electrocardiogram, electromyography, galvanic skin response, and respiration rate. DAPIS provides a real-time visualization of physiological information and a methodology to synchronize the events with ESAT. Lastly, ESAT is a novel method to acquire users' emotional self-assessment in medium-term experiments. After an empirical validation performed on 33 participants, ESAT has proved to be a valid tool which permits to accurately identify the users' emotions.