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An Analysis on the Effect of Phase on the Performance of SSVEP-based BCIs

  • Norbert GauciEmail author
  • Owen Falzon
  • Tracey Camilleri
  • Kenneth Camilleri
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 57)

Abstract

In recent years, brain-computer interface (BCI) systems have emerged as a technology that can support a direct communication pathway between the human brain and external devices. Among the various neurophysiological phenomena that can be used to drive BCI systems, steady-state visual evoked potentials (SSVEPs) have gained increasing popularity because of the high information transfer rate (ITR) and high accuracy that these can provide. In this paper, an investigation on how the inclusion of phase information in the form of a novel proposed feature, the phase-weighted SNR (PWS) feature, can improve the performance of such setups is presented. Improvements in classification accuracies of up to 17% were obtained with the inclusion of phase information when compared to systems that rely solely on amplitude information.

Keywords

Brain-Computer Interface (BCI) Electroencephalography (EEG) Steady-State Visual Evoked Potential (SSVEP) Information Transfer Rate (ITR) 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Norbert Gauci
    • 1
    Email author
  • Owen Falzon
    • 1
  • Tracey Camilleri
    • 2
  • Kenneth Camilleri
    • 2
  1. 1.Centre for Biomedical CyberneticsUniversity of MaltaMsidaMalta
  2. 2.Department of Systems and Control EngineeringUniversity of MaltaMsidaMalta

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