{"ID":2899405,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.02187","arxiv_id":"2507.02187","title":"VergeIO: Depth-Aware Eye Interaction on Glasses","abstract":"There is growing industry interest in creating unobtrusive designs for electrooculography (EOG) sensing of eye gestures on glasses (e.g. JINS MEME and Apple eyewear). We present VergeIO, the first EOG-based glasses that enables depth-aware eye interaction using vergence with an optimized electrode layout and novel smart glass prototype. It can distinguish between four and six depth-based eye gestures with 83-98% accuracy using personalized models in a user study across 20 users and 2,400 gesture instances. It generalizes to unseen users with an accuracy of 77-97% without any calibration. To reduce false detections, we incorporate a motion artifact detection pipeline and a preamble-based activation scheme. The system uses dry sensors without any adhesives or gel, and operates in real time with 3 mW power consumption by the sensing front-end, making it suitable for always-on sensing.","short_abstract":"There is growing industry interest in creating unobtrusive designs for electrooculography (EOG) sensing of eye gestures on glasses (e.g. JINS MEME and Apple eyewear). We present VergeIO, the first EOG-based glasses that enables depth-aware eye interaction using vergence with an optimized electrode layout and novel smar...","url_abs":"https://arxiv.org/abs/2507.02187","url_pdf":"https://arxiv.org/pdf/2507.02187v2","authors":"[\"Xiyuxing Zhang\",\"Duc Vu\",\"Chengyi Shen\",\"Yuntao Wang\",\"Yuanchun Shi\",\"Justin Chan\"]","published":"2025-07-02T22:47:37Z","proceeding":"cs.HC","tasks":"[\"cs.HC\"]","methods":"[]","has_code":false}