Subject-Independent Multi-Class Motor Imagery EEG Classification Using Hybrid CNN–BiLSTM with Channel Attention
The classification of MI-EEG is complex due to the noise, non-stationarity and inter-subject variation of these signals. Some of these challenges are magnified in subject-agnostic settings, where a model must generalise to an unseen user without subject-specific tuning. This study presents a hybrid deep-learning archi...