Using in-game biofeedback to induce player serenity

Video games no longer predominantly emphasize mere entertainment or excitement, they now investigate more complex emotions. As a new dimension of player input, biofeedback (University of Maryland Baltimore Washington Medical Center, 2015) can be used to track a player’s body signals in real-time. This biofeedback can impact a player’s experience during gameplay and making a game affective.  This research aims to design game mechanics to connect game environments with a player’s physiological data, and to thereby trigger a serene gameplay experience. The development process was based on 1) game design strategies for inducing serenity, 2) design methods for biofeedback interaction in video games. Combined with these theoretical approaches, this research followed an iterative design process by prototyping, observations, individual interviews, questionnaires, and data analysis.  The player’s physiological information was detected through three types of sensor: A heart rate (HR) sensor, a galvanic skin response (GSR) sensor, and a webcam with a software library for facial expressions. The game system adopted certain design elements such as color schemes to communicate the biological information these sensors gathered.  There are two hypotheses in this research. One is that the adjustments of the game environment based on the player's physiological information can impact the relationship between the player and the game. The other one is that changing the game environment’s color schemes according to the player’s physiological data can strengthen their emotions.  The final output was a brief (2-5 minutes) 3D exploration game attached with sensors to players. The game contained abstract nature-related visual elements and non-competitive mechanics that were applicable for biofeedback-based interaction. The result of final prototype showed that the nature-related elements and the adjustments of the color schemes in the game helped make players feel serene. The biofeedback-based interactions were effective because they helped some players feel more connected to the game. Ultimately, this work is expected to make the player experience more personal rather than generic and improve the game’s replayability.