Decoding micro-electrocorticographic signals by using explainable 3D convolutional neural network to predict finger movements.
Journal:
Journal of neuroscience methods
PMID:
39151656
Abstract
BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing machine learning models requiring manual feature extraction.