Knowledge-guided EEG Representation Learning

Self-supervised learning, effective in multimedia domains, is equally important for biosignals due to limited labeled data; adapting these methods to biosignal analysis requires novel approaches, as demonstrated by our proposed EEG model, utilizing a state space-based deep learning architecture and a knowledge-guided pre-training objective, resulting in improved embedding representation learning and reduced pre-training data requirements.