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.

Omar Trigui, Wassim Zouch and Mohamed Ben Messaoud . “Anti-noise Capability Improvement of Minimum Energy Combination Method for SSVEP Detection”. International Journal of Advanced Computer Science and Applications (IJACSA) 7.9 (2016). http://dx.doi.org/10.14569/IJACSA.2016.070953

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