VEOS: Vision-based vertical electrooculography inference from monocular periocular video for ocular artefact suppression in EEG

OBJECTIVE: Ocular artefacts from blinks and eye movements remain a persistent obstacle to reliable electroencephalography (EEG), particularly when dedicated electrooculography (EOG) electrodes are unavailable or undesirable. We investigate whether monocular periocular video can provide a vertical EOG (VEOG)-like surrogate for ocular artefact suppression in EEG. Approach. We present VEOS, a video-to-VEOG inference pipeline based on monocular periocular tracking, canthus-defined geometric normalisation, engineered eyelid and iris features, and temporal modelling with a temporal convolutional network (TCN). The inferred VEOG is used as an auxiliary reference in blink-window lagged ridge-regression subtraction of ocular artefacts from EEG. Evaluation used leave-one-subject-out validation on two multimodal datasets: an in-house development dataset (VEOS-Dev; 5 participants with synchronised EEG, EOG and 120 Hz video) and the public Eye-BCI dataset (31 subjects, 63 sessions; high-speed video, EEG and ocular measurements). For centred-window models, a ±ℓ boundary margin prevented temporal leakage between training, validation and test data. Main results. On VEOS-Dev, VEOS achieves median Pearson correlation r = 0.81 to ground-truth VEOG and median blink-onset timing error of 18 ms. On Eye-BCI, the video-only model achieves median r = 0.74, outperforming an eye-tracker baseline. For blink-window cleaning, VEOS suppresses approximately 50% of blink peak-to-peak amplitude on frontal EEG channels, compared with 66% for true VEOG. Cleaning preserves task-relevant EEG structure, including motor imagery mu/beta rhythms, SSVEP spectral signal-to-noise ratio, and P300 morphology. At the participant level, VEOS yields a modest improvement in motor imagery, leaves SSVEP unchanged, and approaches true-VEOG cleaning for P300 spelling (90% vs 91%). Significance. These results show that camera-derived VEOG can act as a useful ocular reference for EEG artefact suppression without additional periocular electrodes. The validation was conducted on controlled recordings and should be interpreted as a best-case demonstration rather than a full validation in unconstrained wearable settings.