Individual-finger motor imagery classification: a data-driven approach with Shapley-informed augmentation
Haneen Alsuradi,
Arshiya Khattak,
Ali Fakhry
et al.
Abstract:Objective. Classifying motor imagery (MI) tasks that involve fine motor control of the individual five fingers presents unique challenges when utilizing electroencephalography (EEG) data. In this paper, we systematically assess the classification of MI functions for the individual five fingers using single-trial time-domain EEG signals. This assessment encompasses both within-subject and cross-subject scenarios, supported by data-driven analysis that provides statistical validation of the neural correlate that… Show more
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