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The largest EEG-based Benchmark for Open Science#

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We report the results of the benchmark study performed in: -The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark

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This study conducts an extensive Brain-computer interfaces (BCI) reproducibility analysis on open electroencephalography datasets, -aiming to assess existing solutions and establish open and reproducible benchmarks for effective comparison within the field. Please note that the results are obtained using Within-Session evaluation. -The results are reported regarding mean accuracy and standard deviation across all folds for all sessions and subjects.

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If you use the same evaluation procedure, you should expect similar results if you use the same pipelines and datasets, with some minor variations due to the randomness of the cross-validation procedure.

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You can copy and use the table in your work, but please **cite the paper** if you do so.

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Motor Imagery#

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Motor Imagery is a BCI paradigm where the subject imagines performing a movement. -Each imagery task is associated with a different class, and each task has its difficulty level related to how the brain generates the signal.

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Here, we present three different scenarios for Motor Imagery classification:

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  1. Left vs Right Hand: We use only the classes Left Hand and Right Hand.

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  2. Right Hand vs Feet: We use only Right Hand and Feet classes.

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  3. All classes: We use all the classes in the dataset, when there are more than classes that are not Left Hand and Right Hand.

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All the results here are for within-session evaluation, a 5-fold cross-validation, over the subject’s session.

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Motor Imagery - Left vs Right Hand#

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Left vs Right Hand: We use only the classes Left Hand and Right Hand.

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