A Novel SSVEP-BCI System for Accurate Early Detection of Glaucoma

This study proposes a brain-computer interface (BCI) system based on steady-state visual evoked potentials (SSVEP) for the early detection of glaucoma. The system achieves objective assessment of visual pathway abnormalities through a head-mounted integrated platform, combining canonical correlation analysis (CCA) algorithm and one-sided hypothesis testing. The model demonstrates an accuracy of 80% and an F1 score of 86% in the test group. The system offers advantages of non-invasiveness, high temporal efficiency (single detection <5 minutes), and portability, providing a new solution for the universal screening of early glaucoma detection.