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Quantifying EEG Measured Task Engagement for use in Gaming Applications

Chi Vi, Jason Alexander, Pourang Irani, Behrad Babaee, Sriram Subramanian, Quantifying EEG Measured Task Engagement for use in Gaming Applications. , University of Bristol. November 2014. PDF, 475 Kbytes.

Abstract

Brain-Computer Interface (BCI) has the potential to revolutionize the gaming industry. However, we have little fundamental understanding of the speed and accuracy with which users can control virtual objects using only their task engagement levels (mental effort activity), of their brain. We present a series of studies to investigate the use of EEG techniques in the context of gaming. We first investigated the accuracy with which users could select a single target from multiple visual states. We found that users able to move quickly and effectively in both directions (increasing engagement/decreasing engagement) for up to five discrete states. In a second study, we found that users take a linearly increasing amount of time to increase and decrease their level of engagement. Finally, we investigated the practicalities of simultaneously using a traditional input device and engagement in a gaming scenario. Experienced users were more accurate in this parallel input task than novices. Based on these experimental results we discuss several engagement-based game design principles.

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