Neurogaming Hackathon 2015 - Pacman Project
Credits to platzhersh for Pacman-Canvas.
Technologies
- OpenBCI
- Python
- Go
- Websockets
- Canvas
- Javascript
OpenBCI has a 4 Channel Inputs, with a 10/20 Scheme Placement
Steady state visually evoked potential. Induced by flashing lights. Frequencies: 8, 10, 12, 15 Hz
Initial Filtering with a Bessel Bandpass Filter (5 - 30 Hz), then goes through a Fast Fourier Transform (FFT)
Predictive Machine Learning Algorithm: Linear discriminant analysis (LDA), Training through calibration
Credit to “Pacman Canvas” by Platzh1rsch
SSVEP game controls, Websocket payloads input, Game controlled by flashing lights. Arrows indicate which direction. Flashing indicates the specified frequency associated with that direction
Team
- Hithesh Reddivari
- Kevin Schiesser
- Glenn Wright
- Jeremy Wong