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This review examines channel selection for EEG-based brain-computer interfaces (BCIs) across four paradigms: motor imagery, motor execution, steady-state visual evoked potentials, and P300. By analyzing 21 studies, the authors identify significant cortical activations and propose a knowledge-based channel selection framework to optimize electrode use, enhance accuracy, and reduce computational complexity. The core channel selection (CCS) subset serves as a reference for EEG researchers, facilitating practic

Author

kodewa4797

Language

EN