A benchamark classification toolbox for Brain-Computer Interface EEG data
Data sets available:
- BCI Compeition III Challenge 2004 (P300 evoked potentials) (http://www.bbci.de/competition/iii/)
- EPFL P300 data set (https://mmspg.epfl.ch/BCI_datasets)
- P300 speller with ALS patients (set #8) (http://bnci-horizon-2020.eu/database/data-sets)
- LARESI inverted face data set (coming soon)
- SSVEP Exoskeleton (https://old.datahub.io/dataset/dataset-ssvep-exoskeleton)
- Tsinghua Sampled sinusoidal Joint Frequency-Phase Modulation SSVEP (http://www.thubci.org/en/?a=nr&id=100)
- San Diego Square Joint Frequnecy-Phase Modulation SSVEP (ftp://sccn.ucsd.edu/pub/cca_ssvep)
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Processing methods available:
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- Feature extraction: --- Downsample --- Multivariate Linear Regression(MLR)
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- classification :
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- LDA
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- Regularized LDA (shrinkage-LDA)
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- SWDLA
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- SVM (LIBSVM)
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- Logistic Regression (LIBLINEAR)
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- Random Forest
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- SVM+
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- Canonical Correlation Analysis based methods : - - - CCA, FilterBank CCA (FBCCA), L1-Multiway CCA, MsetCCA, Individual Template CCA (ITCCA)
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- Task-related Component Analysis (TRCA)
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Run the setup.m script
- Download one of the Datasets (or all) in the list.
- create a new folder inside the Dataset/epochs.
- Run one (or all, one by one) scripts related to each dataset in the dataio folder.
- Run the script "define_approach_ERP.m" for ERP data
- Run the script "define_approach_SSVEP.m" for SSVEP data
coming soon
coming soon