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Computational modeling and application of steady-state visual evoked potentials in brain-computer interfaces

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Paper

Link: https://www.researchgate.net/profile/Yijun-Wang-23/publication/282679100_Computational_modeling_and_application_of_SSVEPs_in_BCIs/links/5618704f08ae6d17308498ea/Computational-modeling-and-application-of-SSVEPs-in-BCIs.pdf
Year: 2015

Summary

  • shows how SSVEP works
  • notes on SSVEP

Learnings

  • SSVEP harmonics were clearly observed within the frequency range that showed an upperbound frequency around 90Hz
  • amplitude of the harmonics decreases when the frequency of the harmonics increases
  • modulating SSVEPs can be categorized into three groups
    • Frequency tracking
    • Phase tracking
    • Attention tracking
  • two stimuli with the same frequency and a 180-degree phase difference can result in two SSVEP signals that are negatively correlated
  • Advanced stimulus coding methods (e.g., mixed frequency and phase coding) can significantly improve the coding efficiency
  • Another important factor affecting BCI performance is user attention. During BCI operation, visual attention needs to be maintained at a high level so that SSVEP parameters are stable across multiple trials.