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jdpigeon/lessonsFromNTXStudentOpenChallenge.md

Created April 12, 2018 14:53
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NeuroTechUofT

  • Encountered performance bottlenecks when running BCI paradigms in Python in real time. Overcame somewhat by using specific data structures such as trees
  • Had to use Muse 2014
  • multi-class motor classification seds estimation approach ? Ran into trouble with source localization using Muse (figures). Found paper using 8 channel EEG to classify hand gestures based on spectral data (freiburg)
  • With P300 speller, encountered significant marker variability that messed up ERP detection.
  • Signal quality issues with motor imagery task (muse?)

MINT

  • Implemented flanker test on Android w/ Muse
  • Looked for alpha and beta suppression in order to evaluate ADD
  • Hard hard time making app "stable"
  • Looks like native Android app

SynapsETS

  • Used muse-io and Unity
  • Sent EEG and EMG data from Unity over UDP to a python script to communicate with RP PI
  • Open source on GitHub

MACtion Potential

  • Tried to build a robotic arm to move right or left depending on motor imagery
  • GitHub for technical overview and code

Merlin NeuroTech

  • Merlin blog and Github for info
  • Moving to support OpenBCI as well
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