The electro-physiological visual feedback screen

SSVEP Brain Hash Function

This project had a goal to research if steady-state visually evoked potential (SSVEP) can be used to create Brain Hash Function Algorithm able to distinguish between unique footprints of each individual brain under specific visual stimulation with electro-physiological visual feedback based on consumer-grade EEG monitoring device.

The project scope consist of two major parts:

  1. Implementation of electro-physiological visual feedback system based on consumer-grade EEG monitoring device. It should perform monitoring of EEG signals in real time and perform preprocessing of received raw EEG signal.

  2. Implementation of advance machine-learning pipeline to automatically extract important features from data stream and perform classification of encoded features. It should perform confident classification of the collected EEG data in order to (a) reliably distinguish signal from noise and (b) reliably distinguish between EEG records collected from different human participants.

The project timeline and results can be found at: ResearchGate

Publications

. arXiv:1708.01167. Applying advanced machine learning models to classify electro-physiological activity of human brain for use in biometric identification, 2017.

Preprint PDF Code Project Source Document