AI RESEARCH
A Domain-Informed Multi-Objective Framework for EEG Channel Selection in Motor Imagery BCIs
arXiv CS.LG
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ArXi:2605.29943v1 Announce Type: cross Motor imagery (MI) classification using electroencephalography (EEG) signals is essential for advancing brain-computer interfaces (BCIs). Traditional EEG channel selection methods often face limitations, such as dependency on single-objective criteria and susceptibility to local optima. To address these challenges, this work proposes a multi-objective optimisation framework that employs non-dominated sorting genetic algorithm, multiple-objective particle swarm optimisation, and a multi-objective evolutionary algorithm based on decomposition.