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EEG data classification using wavelet features selected by Wilcoxon statistics
journal contribution
posted on 2015-07-01, 00:00 authored by Thanh Thi NguyenThanh Thi Nguyen, Abbas KhosraviAbbas Khosravi, Douglas CreightonDouglas Creighton, Saeid NahavandiThis paper introduces a method to classify EEG signals using features extracted by an integration of wavelet transform and the nonparametric Wilcoxon test. Orthogonal Haar wavelet coefficients are ranked based on the Wilcoxon test’s statistics. The most prominent discriminant wavelets are assembled to form a feature set that serves as inputs to the naïve Bayes classifier. Two benchmark datasets, named Ia and Ib, downloaded from the brain–computer interface (BCI) competition II are employed for the experiments. Classification performance is evaluated using accuracy, mutual information, Gini coefficient and F-measure. Widely used classifiers, including feedforward neural network, support vector machine, k-nearest neighbours, ensemble learning Adaboost and adaptive neuro-fuzzy inference system, are also implemented for comparisons. The proposed combination of Haar wavelet features and naïve Bayes classifier considerably dominates the competitive classification approaches and outperforms the best performance on the Ia and Ib datasets reported in the BCI competition II. Application of naïve Bayes also provides a low computational cost approach that promotes the implementation of a potential real-time BCI system.
History
Journal
Neural computing and applicationsVolume
26Issue
5Pagination
1193 - 1202Publisher
SpringerLocation
Berlin, GermanyPublisher DOI
ISSN
0941-0643Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2014, SpringerUsage metrics
Keywords
BCI competition IIEEG signal classificationNaïve Bayes classifierWavelet transformationWilcoxon testScience & TechnologyTechnologyComputer Science, Artificial IntelligenceComputer ScienceNaive Bayes classifierFEATURE-EXTRACTIONNEURAL-NETWORKSIGNAL CLASSIFICATIONTRANSFORMMACHINEArtificial Intelligence and Image Processing
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