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In this paper, we show how a model of human cognition based on ACT-R can be improved to accurately predict cognitive performance under different workload levels. For this purpose, we propose a novel approach which uses an EEG-based workload model to (de-)activate a dummy model which runs in parallel to the actual task model. The dummy model consumes cognitive resources to reflect the effect of workload...
This work describes the development and evaluation of a recognizer for different levels of cognitive workload in the car. We collected multiple biosignal streams (skin conductance, pulse, respiration, EEG) during an experiment in a driving simulator in which the drivers performed a primary driving task and several secondary tasks of varying difficulty. From this data, an SVM based workload classifier...
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