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Real-Time Assessment of Mental Workload with Near-Infrared Spectroscopy: Potential for Human-Computer Interaction

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Abstract

We have used machine learning techniques to analyze functional near-infrared spectroscopy (fNIRS) data from the brain of human subjects to classify different levels of mental workload. Preliminary results show potential for fNIRS in human-computer interaction research.

© 2008 Optical Society of America

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