title: Improving classification accuracy using fuzzy method for BCI signals.
abstract: Electroencephalograph (EEG) signals feature extraction and processing is one of the most difficult and important part in the brain-computer interface (BCI) research field. EEG signals are generally unstable, complex and have low signal-noise ratio, which is difficult to be analyzed and processed. To solve this problem, this paper disassembles EEG signals with the empirical mode decomposition (EMD) algorithm, extracts the characteristic values of the major intrinsic mode function (IMF) components, and then classifies them with fuzzy C-means (FCM) method. Also, comparison research is done between the proposed method and several current EEG classification methods. Experimental results show that the classification accuracy based on the EEG signals of the second BCI competition in 2003 is up to 78%, which is superior to those of the comparative EEG classification methods.
authors.affiliation: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650504, China Department of Electrical & Electronics Engineering, Chengdu Technological University, Chengdu 611730, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Wei
authors.affiliation: Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650504, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Jun
authors.affiliation: Department of Electrical & Electronics Engineering, Chengdu Technological University, Chengdu 611730, China.
authors.forename: Sun
authors.initials: S
authors.lastname: Lin
authors.affiliation: School of information science and engineering, Yunnan University, Kunming 650091, China.
authors.forename: Li
authors.initials: L
authors.lastname: Hong
mesh_terms: D000328:Adult; D000465:Algorithms; D062207:Brain-Computer Interfaces; D004569:Electroencephalography / Q000379:methods*; D019054:Evoked Potentials, Motor / Q000502:physiology*; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D009044:Motor Cortex / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Brain-computer interface (BCI); fuzzy C-means (FCM); intrinsic mode function (IMF)