Predicting Multitasking Performance: An EEG- and Eye Movement-Based Dynamic Bayesian Network
This study proposes a probabilistic model using neural and physiological responses to continuously predict performance during multitasking. Though multitasking performance is known to be time-varying depending on task demand, there is limited research modeling temporal changes in multitasking performance. We applied a dynamic Bayesian network (DBN) to predict multitasking performance while recording participants’ eye movements and electroencephalogram (EEG) band power during the Multi-Attribute Task Battery II task. Our DBN model including multimodal eye...
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