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We applied Random Forest (RF) classifiers on electroencephalographic (EEG) data of right hand vs. Feet Motor Imagery (MI) we achieved a cross-validation classification accuracy of 79% on average over 10 participants. We found mu and beta band measured at position C3 most important for classification, which is in line with current state of knowledge.

Author

Frontiers

Language

EN