Brain Computer Interface

/ Team Research /
Neuroscience Study / Statistics Algorithm Study / Hardware Implementation / Programming : Matlab, C++ /

Purpose : Implementing a CCA algorithm built-in system on an ARM-based embedded system for SSVEP applications

Steady state visually evoked potential (SSVEP) are signals that are natural responses to visual stimulation at specific frequencies. When the retina is excited by a visual stimulus ranging from 3.5 Hz to 75 Hz, the brain generates electrical activity at the same (or multiples of) frequency of the visual stimulus. This phenomenon can be used for disables, elders, or unmovable situation such as the pilot in the cabin; we design and realize a method to catalyze the development of the noninvasive portable brain-computer interaction devices by implanting the Canonical Correlation Analysis on Arm based embedded system. Arm based device such as mobile phone or wearable devices can detect and extract the SSVEP from users to work as the control signal. In this research, we implemented and tested our work on the Andes FPGA board, the result leads to a cost effective way to sense brain waves activities. In my opinion, brain wave sensing as input signal may be popularized shortly for the growth of virtual reality headsets and cheaper hardware cost. It will bring a more direct way of human-computer interaction.

link to pdf