Yunze Li

Multi-Level Spatial-Temporal Adaptation Network for Motor Imagery Classification

Electroencephalogram (EEG) signals for motor imagery (MI) are easily influenced by the environment and the state of the subject, which exhibit temporal and spatial variance. And this variance is more significant across subjects and sessions, which imposes limitations on the cross-domain MI tasks. To…