VR-FOCUS: Investigating eye tracking during a virtual reality N-back task as a predictor of cognitive load in chronic pain

Immersive virtual reality (VR) is a promising medium for adaptive pain therapeutics, but objective markers of cognitive load suitable for real-time adaptation remain insufficiently characterised in people living with chronic pain. This study evaluated whether eye tracking embedded within a consumer-available VR system provides signatures of cognitive load during a VR N-back task in healthy controls and a pragmatic chronic musculoskeletal pain cohort. A total of 84 participants (42/group) completed five levels (Baseline to 4-Back) while ocular responses were recorded. Performance declined and subjective workload increased with higher N-back levels, confirming successful manipulation of cognitive demand. In mixed-effects models, larger pupil diameter and higher blink rate were associated with higher task level and workload ratings after covariate adjustment. Logistic regression using summary pupil and blink features showed limited discrimination of load (1-Back vs 4-Back), with near-chance accuracies (0.51–0.60). In contrast, time-series classifiers exploiting temporal structure achieved higher participant-level accuracy in healthy controls (0.81–0.87) and in chronic pain (0.60–0.66) using pupil diameter alone. Adding blinks produced small, reproducible improvements in model accuracy for the chronic pain group. These findings support VR-embedded eye tracking for cognitive load estimation, but suggest closed-loop applications in chronic pain will require personalised models.