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Neurogaming Hackathon 2015 - Pacman Project

License: MIT License

PHP 0.99% HTML 5.95% JavaScript 68.04% CSS 7.08% Go 17.16% Python 0.78%

nghack-pacman's Introduction

Pacman with OpenBCI

Neurogaming Hackathon 2015 - Pacman Project

Credits to platzhersh for Pacman-Canvas.

Pacman screenshot

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

nghack-pacman's People

Contributors

jermspeaks avatar

Watchers

James Cloos avatar

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