FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network

arXiv:2403.03526v1 Announce Type: cross
Abstract: Brain-computer interface (BCI) technology facilitates communication between the human brain and computers, primarily utilizing electroencephalography (EEG) signals to discern human intentions. Although EEG-based BCI systems have been developed for paralysis individuals, ongoing studies explore systems for speech imagery and motor imagery (MI). This study introduces FingerNet, a specialized network for fine MI classification, departing from conventional gross MI studies. The proposed FingerNet could extract spatial and temporal features from EEG signals, improving classification accuracy within …

abstract arxiv bci brain brain-computer interface communication computer computers cs.lg decoding deep neural network eeg eess.sp explore human network neural network paralysis q-bio.nc speech studies systems technology type