Passive brain-computer interfaces are designed to use brain activity as an additional input, allowing the adaptation of the interface in real time according to the users mental state. While most current brain computer interface research (BCI) is designed for direct use with disabled users, I focus my research on passive BCIs for healthy users. The goal of my dissertation is to employ functional near-infrared spectroscopy (fNIRS), a non-invasive brain measurement device, to augment an interface so it uses brain activity measures as an addi-tional input channel. I have measured and classified brain signals that are interesting in HCI context, such as mental workload and difficulty level of a task. My future work will focus on creating an interface that re-sponds to one of those measures by adapting the in-terface. By combining brain signal measured with an adaptive interface I expect to contribute a functional passive brain-computer interface that measures and adapts to the users brain signal.
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