Deep learning of resting-state electroencephalogram signals for three-class classification of Alzheimer’s disease, mild cognitive impairment and healthy ageing

• Published in: Journal of neural engineering Vol. 18; no. 4; pp. 46087 - 46099
• Main Authors: Huggins, Cameron J, Escudero, Javier, Parra, Mario A, Scally, Brian, Anghinah, Renato, Vitória Lacerda De Araújo, Amanda, Basile, Luis F, Abasolo, Daniel
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.08.2021
• Subjects: Alzheimer’s disease; biomedical signal processing; classification; deep learning; electroencephalogram (EEG); mild cognitive impairment (MCI)

Objective. This study aimed to produce a novel deep learning (DL) model for the classification of subjects with Alzheimer’s disease (AD), mild cognitive impairment (MCI) subjects and healthy ageing (HA) subjects using resting-state scalp electroencephalogram (EEG) signals. Approach. The raw EEG data...