BENDR for BCI: UToronto’s BERT-Inspired DNN Training Approach Learns From Unlabelled EEG Data
University of Toronto researchers propose a BERT-inspired training approach as a self-supervised pretraining step to enable deep neural networks to leverage newly and publicly available massive EEG (electroencephalography) datasets for downstream brain-computer-interface (BCI) applications.