EEG-based Assessment of Long-Term Vigilance and Lapses of Attention using a User-Centered Frequency-Tagging Approach

Abstract

ObjectiveSustaining vigilance over extended periods is crucial for many critical operations but remains challenging due to the cognitive resources required. Fatigue and other factors contribute to fluctuations in vigilance, causing attentional focus to drift from task-relevant information. Such lapses of attention, common in prolonged tasks, lead to decreased performance and missed critical information, with potentially serious consequences. Identifying physiological markers that predict inattention is key to developing preventive strategies. ApproachPrevious research has established electroencephalography (EEG) responses to periodic visual stimuli, known as steady-state visual evoked potentials (SSVEP), as sensitive markers of attention. In this study, we evaluated a minimally intrusive SSVEP-based approach for tracking vigilance in healthy participants (N = 16) during two sessions of a 45-minute sustained visual attention task (Mackworths clock task). A 14 Hz frequency-tagging flicker was either superimposed on the task or absent. Main resultsResults revealed that SSVEP responses were lower prior to lapses of attention, while other spectral EEG markers, such as frontal theta and parietal alpha activity, did not reliably distinguish between detected and missed attention probes. Importantly, the flicker did not affect task performance or participant experience. SignificanceThis non-intrusive frequency-tagging method provides a continuous measure of vigilance, effectively detecting attention lapses in prolonged tasks. It holds promise for integration into passive brain-computer interfaces, offering a practical solution for real-time vigilance monitoring in high-stakes settings like air traffic control or driving. Highlights- Fluctuations in the SSVEP response to a continuous frequency-tagging flicker presented throughout a 45-minutes long vigilance task was used to characterize lapses of attention - The frequency-tagging flicker superimposed to the task was designed to be minimally intrusive thanks to its low luminance and low contrast - Neither the user experience nor the task performance were altered by the presence of the frequency-tagging flicker - The SSVEP response outperformed measures of individual alpha peak and theta band activity in the distinction of attentional lapses (missed events) from successful target event identification - The present findings have implications for the design of Human-Computer Interfaces aimed at monitoring (in)attention during the performance of monotonous routines (e.g., surveillance, driving,...)