SSVEP Brain Hash Function

Our goal is to create Brain Hash Algorithm able to produce robust distinction between EEG signals of different humans under electro-physiological visual feedback based on steady-state visually evoked potential (SSVEP). It can be applied at variety of tasks from user authentication at online web services to user identification for physical access control systems.

Applying advanced machine learning models to classify electro-physiological activity of human brain for use in biometric identification.

In this article we present the results of our research related to the study of correlations between specific visual stimulation and the elicited brain's electro-physiological response collected by EEG sensors from a group of participants. We will look at how the various characteristics of visual stimulation affect the measured electro-physiological response of the brain and describe the optimal parameters found that elicit a steady-state visually evoked potential (SSVEP) in certain parts of the cerebral cortex where it can be reliably perceived by the electrode of the EEG device.