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

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.

@article{Trigui2016,
  title     = {Anti-noise Capability Improvement of Minimum Energy Combination Method for SSVEP Detection},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {9},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Omar Trigui and Wassim Zouch and Mohamed Ben Messaoud},
  doi       = {10.14569/IJACSA.2016.070953},
  url       = {https://doi.org/10.14569/IJACSA.2016.070953}
}