Using natural head movements to continually calibrate EOG signals

Electrooculography (EOG) is the measurement of eye movements using surface electrodes adhered around eye. EOG systems can be designed to have an unobtrusive form-factor that ideal for tracking in free-living over long durations, but relationship between voltage and gaze direction requires frequent re-calibration as skin-electrode impedance retinal adaptation vary time. Here we propose a method automatically calibrating EOG-gaze by fusing signals with gyroscopic measurements head movement whenever vestibulo-ocular reflex (VOR) active. The fusion executed recursive inference on hidden Markov model accounts all rotational degrees-of-freedom uncertainties simultaneously. This enables continual calibration natural while minimizing impact sensor noise. No external devices like monitors or cameras are needed. On average, our method’s estimates deviate 3.54° from those industry-standard desktop video-based tracker. Such discrepancy par latest mobile video trackers. Future work focused detecting moments VOR free-living.