Virtual agent interactions
Recognizing Facial Expressions Using Model-Based Image Interpretation
Multimodal Signals: Cognitive and Algorithmic Issues
Information filtering, expertise and cognitive load
FAC'07 Proceedings of the 3rd international conference on Foundations of augmented cognition
FAC'07 Proceedings of the 3rd international conference on Foundations of augmented cognition
Usability engineering for the adaptive web
The adaptive web
Facial expression recognition for human-robot interaction: a prototype
RobVis'08 Proceedings of the 2nd international conference on Robot vision
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Information filtering is an effective tool for improving performance but requires real-time information about the user's changing cognitive states to determine the optimal amount of filtering for each individual at any given time. Current research at the Adaptive Multimodal Interactive Laboratory assesses the user's cognitive ability and cognitive load from physiological measures including: eye tracking, heart rate, skin temperature, electrodermal activity, and the pressures applied to a computer mouse during task performance. A model of adaptive information filtering is proposed that would improve learning and task performance by optimizing the human-computer interface based on real-time information of the user's cognitive state obtained from these passive physiological measures.