Domain-aware domain–class adaptation network for motor execution to motor imagery EEG classification

IntroductionMotor imagery (MI) is one of the most widely used paradigms in electroencephalogram (EEG)-based brain–computer interfaces (BCIs). In recent years, deep learning and transfer learning techniques have been increasingly adopted to further improve MI-EEG decoding performance, thereby facilitating the practical deployment of BCIs. In transfer learning, the similarity between the source and target domains is a critical factor influencing its effectiveness. Given the analogous cortical acti