Deep Learning in EEG: Advance of the Last Ten-Year Critical Period

Deep learning has achieved excellent performance in a wide range of domains, especially speech recognition and computer vision. Relatively less work been done for electroencephalogram (EEG), but there is still significant progress attained the last decade. Due to lack comprehensive topic widely covered survey deep EEG, we attempt summarize recent provide an overview, as well perspectives future developments. We first briefly mention artifacts removal EEG signal then introduce models that have utilized processing classification. Subsequently, applications are reviewed by categorizing them into groups, such brain–computer interface, disease detection, emotion recognition. They followed discussion, which pros cons presented directions challenges proposed. hope this article could serve summary past beginning further developments achievements studies based on learning.