Proposes a deep multi-scale neural network for EEG signal representation learning.
problem Capturing multi-frequency properties in EEG signals for better brain-computer interface.
method A novel deep multi-scale neural network that discovers feature representations in multiple frequency/time ranges and extracts spatial relationships.
result Improved performance in various active/passive BCI datasets compared to state-of-the-art methods.