Abstract
Cognitive load measurement is a challenging research area that many methods have been provided to get more accurate results. Limitations which are pointed by Cognitive Load Theory (CLT) make this area both special and difficult. Subjective, behavioral, and physiological methods all have some advantages and disadvantages. That’s why the use of combined methods has been increasing to make more accurate and better cognitive workload predictions. Technologies such as eye tracking systems, physiological and physical parameters monitoring systems are able to support the relevant researches in this area. On the other hand, there have been some developments which aim different benefits. One of them is Brain-Computer Interface (BCI) technology that works based on Electroencephalography (EEG), detect P300 component of Event Related Potentials and Steady State Evoked Potentials (SSVEP) and offer motor imagery applications. Therefore, they have potential benefits to support cognitive workload measurement methods. In this study, relationships between brain potentials and cognitive workload are researched. Further, opportunities to create new combined cognitive workload measurement methods including BCI, eye-tracking, physiological, and physical parameters are discussed.
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