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Drivers have numerous demands and distractions while navigating the vehicle, both on the road as well as from people and technology within the vehicle. As new interfaces and technologies are introduced into vehicles, it is critical to assess the cognitive workload that the driver is experiencing to ensure safe operation of the vehicle. An understanding of the changing cognitive state of a driver in real-time can inform the design of in-vehicle interfaces.

We propose using functional near-infrared spectroscopy (fNIRS) to measure brain activity during driving tasks. Functional NIRS is a relatively new brain sensing technology that is portable and non-invasive, making it possible to sense brain activity in environments that would not be possible using most traditional imaging techniques. This provides us with the opportunity to better understand changes in cognitive state during mobile tasks, such as driving. Our research aims to integrate fNIRS into an existing driving test bed and explore signal processing and classification algorithms to study the sensitivity of fNIRS brain sensing to changes in the driver’s workload level in real-time.
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