The study of the relationship between electro-oculogram and the features of closed eye motion

The study emphasized on the possibility of using computer vision to synthesize the electro-oculogram (EOG) signals acquired from the contact electrode measuring. The synchronized image frames of the closed eye status and the corresponding EOG signals were sent into the re-sampling module to be aligned. Four categories of images features including spatial domain, frequency domain, statistics, and local entropy analysis were adopted to transfer the two-dimensional image into a time sequential signal and to make the comparison between EOG signals and corresponding features. The correlation analysis was recruited to qualitatively identify the relationship of EOG signals and closed eyeball moving images. The simulation results indicates that the local entropy feature has a close correspondence with EOG signal; as a result, the proposed fuzzy membership function based on the local entropy blocks might deliver a non-invasively synthesized EOG signal in sleep research practically.