Motor imagery (MI) electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with the outside world via external devices. Recent deep learning…
read moreIn stroke rehabilitation, motor imagery based on a brain–computer interface is an extremely useful method to control an external device and utilize neurofeedback. Many studies have reported on the classification…
read moreEEG-based brain computer interface (BCI) systems have demonstrated potential to assist patients with devastating motor paralysis conditions. However, there is great interest in shifting the BCI trend toward applications…
read moreWe provide an open access dataset for hybrid brain-computer interfaces (BCIs) using electroencephalography (EEG) and near-infrared spectroscopy (NIRS). For this, we conducted two BCI experiments (left vs. right hand…
read moreDistinctive EEG signals from the motor and somatosensory cortex are generated during mental tasks of motor imagery (MI) and somatosensory attentional orientation (SAO). In this study, we hypothesize that…
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