Near-invisible c-VEP-based passive BCI for mental workload monitoring

Abstract

Objective. Flickering visual stimuli, either periodic steady-state visual evoked potential (VEP) or aperiodic code-based VEP (c-VEP), have shown strong potential for implementing reactive brain–computer interfaces (BCIs) and enabling hands-free interaction. Yet, their adaptation to passive BCIs (pBCIs) remains limited, largely due to the distracting nature of flickers and its impact on visual comfort. Approach. In this study, we introduce an unobtrusive approach that embeds near–invisible, texture-based flickers over regions of interest in the user interface, combined with a c-VEP pBCI pipeline to assess mental workload. We validated the approach in two experiments: (i) within an ecologically valid multitasking microworld of flying, and (ii) in a flight Simulator, where cognitive workload was systematically varied across three levels. Main results. Results at the group level disclosed that the amplitude of visual event-related potentials was significantly reduced under higher workload, providing an insightful neural marker for workload assessment. Moreover, results demonstrated that the proposed pipeline successfully enabled the derivation of indexes sensitive to workload-related modulation. Significance. These findings highlight the potential of textured flicker and c-VEP-based pBCIs for monitoring cognitive workload in complex operational environments.