Cognitive Load Estimation

Подробнее о видео

This video presents theoretical details and applications of cognitive load estimation using ocular and EEG parameters for eXtended Reality applications. Cognitive load estimation has a rich history although what is cognitive load or the very definition is often debatable among scientists. The most popular theory on cognitive load is in education technology sector. However, in most literature cognitive load is estimated through comparison or correlation of various physiological parameters - the most common ones are based on EEG and eye gaze metrics.
We identified a research gap on using existing metrics for AR/VR applications. We also require parameters measurable by stand alone devices with higher external validity. Unlike many EEG studies, we could not use high end EEG systems which often requires sophisticated grounding and we did not want to remove EEG artefacts corresponding to any physical activity to make the metrics usable in real time applications.
We worked with Dr Aumkar Shah, happens to be a gold medalist from AIIMS (New Delhi) and he defined a set of EEG metrics . We also coded and cross checked a set of programs to differentiate fixations and saccades from eye gaze locations based on a velocity threshold. Next, we used this battery of tests to three different applications and used these ocular and EEG metrics to compare between AR/MR/VR implementations and correlate them with non-physiological metric of cognitive load.
Selected Publications