Masanao Obayashi, Takuya Geshi, Takashi Kuremoto, Shingo Mabu
Available Online 1 March 2016.
spatio-spectral filter, EEG, classification, .optimization, mutual information, common spatial filter
How to select the appropriate frequency band to classify EEG signal by motor imagery is discussed in this paper. Our proposal is an improvement of the conventional Bayesian Spatio-Spectral Filter Optimization (BSSFO). Defect of BSSFO is on the way to generate the renewal particle of the filter bank, such a random number generation. To avoid a local optimum, an evolutional update method of particles is introduced. It is shown that performance of the EEG classification ability is improved.
© 2013, the Authors. Published byALife Robotics Corp. Ltd
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).