Data Constraints and Performance Optimization for Transformer-Based Models in EEG-Based Brain-Computer Interfaces: A Survey
Aigerim Keutayeva,
Berdakh Abibullaev
Abstract:This work reviews the critical challenge of data scarcity in developing Transformerbased models for Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs), specifically focusing on Motor Imagery (MI) decoding. While EEG-BCIs hold immense promise for applications in communication, rehabilitation, and human-computer interaction, limited data availability hinders the use of advanced deep-learning models such as Transformers. In particular, this paper comprehensively analyzes three key strategies to a… Show more
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