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Express"],"published-print":{"date-parts":[[2026,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    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.\n                    <jats:italic>Approach.<\/jats:italic>\n                    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. 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\u2013brain\u2013computer interface (BCI) dataset (31 subjects, 63 sessions; high-speed video, EEG and ocular measurements). For centred-window models, a\n                    <jats:inline-formula>\n                      <jats:tex-math>\n                        \n                      <\/jats:tex-math>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                          <mml:mo>\u00b1<\/mml:mo>\n                          <mml:mi>\u2113<\/mml:mi>\n                        <\/mml:mrow>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    boundary margin prevented temporal leakage between training, validation and test data.\n                    <jats:italic>Main results.<\/jats:italic>\n                    On VEOS-Dev, VEOS achieves median Pearson correlation\n                    <jats:inline-formula>\n                      <jats:tex-math>\n                        \n                      <\/jats:tex-math>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                          <mml:mi>r<\/mml:mi>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>0.81<\/mml:mn>\n                        <\/mml:mrow>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    to ground-truth VEOG and median blink-onset timing error of 18 ms. On Eye\u2013BCI, the video-only model achieves median\n                    <jats:inline-formula>\n                      <jats:tex-math>\n                        \n                      <\/jats:tex-math>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" overflow=\"scroll\">\n                        <mml:mrow>\n                          <mml:mi>r<\/mml:mi>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>0.74<\/mml:mn>\n                        <\/mml:mrow>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    , 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 (MI) mu\/beta rhythms, steady-state visual evoked potentials (SSVEP) spectral signal-to-noise ratio, and P300 morphology. At the participant level, VEOS yields a modest improvement in MI, leaves SSVEP unchanged, and approaches true-VEOG cleaning for P300 spelling (90% vs 91%).\n                    <jats:italic>Significance.<\/jats:italic>\n                    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.\n                  <\/jats:p>","DOI":"10.1088\/2057-1976\/ae83bb","type":"journal-article","created":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T22:47:50Z","timestamp":1782773270000},"page":"045018","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["VEOS: vision-based vertical electrooculography inference from monocular periocular video for ocular artefact suppression in EEG"],"prefix":"10.1088","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1980-3618","authenticated-orcid":true,"given":"Peter","family":"Redmond","sequence":"first","affiliation":[{"name":"Dublin City University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6916-6770","authenticated-orcid":false,"given":"Andrew","family":"Fleury","sequence":"additional","affiliation":[{"name":"Dublin City University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6173-6607","authenticated-orcid":false,"given":"Tom\u00e1s","family":"Ward","sequence":"additional","affiliation":[{"name":"Dublin City University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"266","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"key":"bpexae83bbbib1","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/12\/3\/031001","type":"journal-article","volume":"12","author":"Urig\u00fcen","year":"2015","journal-title":"J. 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