Real Time fNIRS Classification for BCIs

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 user’s mental state. While most current brain computer interface research (BCI) is designed for direct use with disabled users, our research focuses on passive BCIs for healthy users. We employ functional near-infrared spectroscopy (fNIRS), a non-invasive brain measurement device, to augment an interface so it uses brain activity measures as an additional input channel. Past research has measured and classified brain signals that are interesting in HCI context, such as mental workload and difficulty level of a task. Current work focuses on developing a real time fNIRS classification system and creating an interface that responds to one of those measures by adapting the interface.