Anti-noise Capability Improvement of Minimum Energy Combination Method for SSVEP Detection

Abstract

Minimum energy combination (MEC) is a widely used method for frequency recognition in steady state visual evoked potential based BCI systems. Although it can reach acceptable performances, this method remains sensitive to noise. This paper introduces a new technique for the improvement of the MEC method allowing ameliorating its Anti-noise capability. The Empirical mode decomposition (EMD) and the moving average filter were used to separate noise from relevant signals. The results show that the proposed BCI system has a higher accuracy than systems based on Canonical Correlation Analysis (CCA) or Multivariate Synchronization Index (MSI). In fact, the system achieves an average accuracy of about 99% using real data measured from five subjects by means of the EPOC EMOTIVE headset with three visual stimuli. Also by using four commands, the system accuracy reaches 91.78% with an information-transfer rate of about 27.18 bits/min.

Authors and Affiliations

Omar Trigui, Wassim Zouch, Mohamed Messaoud

Keywords

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  • EP ID EP149414
  • DOI 10.14569/IJACSA.2016.070953
  • Views 65
  • Downloads 0

How To Cite

Omar Trigui, Wassim Zouch, Mohamed Messaoud (2016). Anti-noise Capability Improvement of Minimum Energy Combination Method for SSVEP Detection. International Journal of Advanced Computer Science & Applications, 7(9), 393-401. https://europub.co.uk/articles/-A-149414