Designing Games in Conjunction with Psychophysiological Data with Myat Aung

Biosignals monitoring eyes, brain, and muscle function have shown a lot of potential for a more objective understanding of people in different contexts. In recent years, games researchers and studios in particular have been exploring the use of biosignals for understanding player experience. There are developing technologies and ideas for the use of biosignals to improve game design or even develop live adaptive systems to optimise games for a designer’s goals. However, the use of any biosignals have historically involved significant problems with the complexity of data processing and interpretation.
Many of these problems are a consequence of ill-suited design that has not taken adequate consideration for the intricacies of acquiring appropriate biosignal data to begin with. These problems are further accentuated by the limitations of current technology, and debatable empirical understanding of such signals.
In this talk, I will discuss my experiences working with such data in games research. I will detail experimental problems for working with different biosignals, with particular focus on pupillometry and eye tracking. Drawing from recent experiences in using the commercial game ‘Don’t Starve’ as a stimulus, I will discuss techniques for processing, exploring, and interpreting the multitudes of data acquired during my experiments.
Traditionally, artistic intent and scientific, empirical design are considered antagonists for one another. Given this, in addition to implications for empirical research using this data, I will also talk about my current work designing and developing a game which accounts for such problems, while considering what it means for a ‘stimuli’ game to be a research or toy game. It is my goal to depart a better understanding of general, necessary design considerations when using biosignals in both academic and commercial contexts.
My work provides some context for the promises of these so called objective’ methods, but also highlights the significant investment that is still needed in basic research to understand how to effectively use these signals in games for the real world.

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