Package with tools for classification of electroencephalography (EEG) data. Feature extraction techniques such as Fourier Transform and Continuous Wavelet Transform (CWT) are available. Support Vector Machines (SVM) can be used to classify the extracted features. An algorithm using Analysis of Variance (ANOVA), False Discovery Rate (FDR), and SVM is available to feature selection. Additionally, the package contains functions to plot data and features.
|Author||Murilo Coutinho Silva (University of Brasilia, Brazil), George Freitas von Borries (University of Brasilia, Brazil)|
|Date of publication||2014-06-22 15:48:01|
|Maintainer||Murilo Coutinho Silva <email@example.com>|
|License||GPL (>= 2)|
classifyEEG: Classifies new data
easyFeatures: Choosing Features
eegAnalysis-package: Feature selection and classification of...
FeatureEEG: Automatic Feature Selection
featureSelection: Feature Selection Algorithm
plotEEG: Plot EEG data
plotwindows: Plot statistics calculated by windows
randEEG: EEG simulation
svmEEG: Support Vector Machines