Feature fusion and WOA-GWO optimization for Alzheimer’s disease detection with sparse EEG channels
Yanqiu Che
Alzheimer’s Disease (AD) is a neurodegenerative disorder with insidious onset, making early diagnosis challenging. Electroencephalogram (EEG) is a promising noninvasive tool for AD diagnosis, but high-density EEG configurations cause computational burdens and hinder clinical translation. Thus, developing an efficient sparse EEG channel selection method with high classification accuracy is urgent for AD auxiliary diagnosis. This study proposes a multi-strategy enhanced Whale Optimization Algorith