Leveraging fNIRS to Evaluate Workload for Adaptive Training in Virtual Reality

TL;DR

This study validates fNIRS as a neuro-ergonomic measure of cognitive load during VR training, showing it reflects intrinsic workload and correlates with NASA TLS measures, enabling adaptive training systems.

Contribution

It demonstrates that fNIRS can reliably measure different types of cognitive load in VR training, supporting adaptive training based on neurophysiological data.

Findings

fNIRS activation in prefrontal cortex and angular gyrus correlates with intrinsic workload

fNIRS results align with NASA TLS measures of mental workload

Less brain activity observed for extraneous load, mainly in the right angular gyrus

Abstract

Advance in technology offer the potential for future adoption of a combination of virtual reality (VR) and real-time adaptivity to enhance training and education. Providing a valid neuro-ergonomic measure of cognitive load can enable an adaptive training regime to continuously adjust tas difficulty to an optimal level as training progresses. The current study validated the functional near-infrared spectroscopy (fNIRS) measure of cognitive load to reflect the demands of two different forms of lad within Cognitive Load Theory: extraneous and intrinsic to he task to be mastered. Thirty-six participants completed a VR shape assembly training task followed by a test of their skill retention They wore near-full head coverage fNIRS and provided subjective ratings of ther workload. The fNIRS findings largely corroborate intrinsic workload literature with significant activation in cortical regions (dorsolateral and rostral prefrontal cortex and left angular gyrus) associated with working memory, short term memory buffers, multisensory integration, and attention. These fNIRS results were tracked closely by NASA TLS measures of mental workload. The results also revealed far less brain activity associated with extraneous load, namely just the right angular gyrus, deemed irrelevant to the mastery of the task.