Development of a transformation model to analyze horizontal saccades using electrooculography through correlation between video-oculography and electrooculography

Saccadic eye movements are established biomarkers in neuroscience and clinical neurology, where video-oculography (VOG) remains the gold standard. However, VOGs high cost, bulky equipment, and poor portability restrict its clinical utility. Electrooculography (EOG) offers a promising alternative by detecting cornea-retinal potential changes during eye movements. To enable quantitative saccadic analysis using EOG as a VOG alternative, this study develops and validates a mathematical transformation model converting EOG data into VOG-equivalent values. A prospective observational study was conducted on 4 healthy adults without neurological or sleep disorders. Horizontal saccades were recorded simultaneously using EOG and VOG during controlled gaze shifts. EOG peak saccadic velocity was derived from voltage change rate, whereas VOG was calculated from angular displacement over time. A derivation dataset of fixed horizontal saccades ({+/-}20{degrees}) formulated the transformation model, achieving a strong correlation coefficient (r = 0.95 rightward, r = 0.93 leftward, p < 0.0001). Multiple filter settings were evaluated, and 0.3 Hz high-pass and 35 Hz low-pass filtering were identified as optimal. The fixed horizontal saccades derived model was applied to a validation dataset of random horizontal saccades, confirming robustness across saccades without significant differences from VOG measurements. These findings establish EOGs feasibility for quantitative analysis of horizontal saccades and provide a validated transformation model. By systematically optimizing filtering parameters, this approach enables EOG as a cost-effective VOG alternative while maintaining high-precision measurement accuracy.