Emotion-Driven Music and IoT Devices for Collaborative Exer-Games - Pedro Álvarez; Jorge García de Quirós; Javier Fabra (Applied Sciences, 2024)
Exer-games are interactive experiences in which participants engage in physical exercises to achieve specific goals. Some of these games have a collaborative nature, wherein the actions and achievements of one participant produce immediate effects on the experiences of others. Music serves as a stimulus that can be integrated into these games to influence players’ emotions and, consequently, their actions. In this paper, a framework of music services designed to enhance collaborative exer-games is presented. These services provide the necessary functionality to generate personalized musical stimuli that regulate players’ affective states, induce changes in their physical performance, and improve the game experience. The solution requires to determine the emotions that each song may evoke in players. These emotions are considered when recommending the songs that are used as part of stimuli. Personalization seeds based on players’ listening histories are also integrated in the recommendations in order to foster the effects of those stimuli. Emotions and seeds are computed from the information available in Spotify data services, one of the most popular commercial music providers. Two small-scale experiments present promising preliminary results on how the players’ emotional responses match the affective information included in the musical elements of the solution. The added value of these affective services is that they are integrated into an ecosystem of Internet of Things (IoT) devices and cloud computing resources to support the development of a new generation of emotion-based exer-games.