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Cognitive Load Inference Using Physiological Markers in Virtual Reality

IEEE via YouTube

Overview

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This IEEE conference talk presents groundbreaking research on predicting cognitive load in virtual reality environments using physiological markers. Learn about a large-scale study (N=738) that collected behavioral and physiological measures under varying cognitive load conditions in VR. Discover how researchers developed an AI model capable of real-time cognitive load prediction on a continuous scale from 0-1, complete with quantified prediction uncertainty. Explore the released dataset from 100 participants featuring multiple sensor recordings (pupillometry, eye-tracking, pulse plethysmography), self-reported cognitive effort, task performance metrics, and demographic information. Part of the "Cognitive Load, Attention, and Perception" session at IEEE VR 2025, this 10-minute presentation showcases collaborative work from researchers at HP Labs, HP Inc., PG&E, Samsung Research America, and Stanford University.

Syllabus

Cognitive Load Inference Using Physiological Markers in Virtual Realit...

Taught by

IEEE Virtual Reality Conference

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