BAFTCNet: A model for motor imagery decoding based on EEG principles and attention mechanisms

Key Points

• Motor imagery decoding achieved high accuracy, indicating effectiveness of the EEG-based model.
• The BAFTCNet model improved performance metrics compared to traditional methods, reaching a notable accuracy level.
• Analysis involved EEG signal processing with integrated attention mechanisms to enhance decoding precision.
• This model may enable more effective brain-computer interfaces, highlighting the need for further validation.