semantic_scholarProceedings of the International Conference on Neuromorphic Systems2026-08-04
WSST-Based Time--Frequency Representation for CNN-Based Dementia Classification from EEG
Salleh Sonko, Wael Korani, Mohamed Islam Houssam, Gahangir Hossain
TL;DR: A compact 2D convolutional neural network framework based on wavelet synchrosqueezing transform (WSST) time–frequency (TF) representations for EEG-based dementia classification demonstrates that the WSST-based representation provides an effective and robust input for CNN-based dementia classification under strict subject-disjoint validation.
Electroencephalography (EEG)-based discrimination of Alzheimer’s disease (AD), frontotemporal dementia (FTD), and cognitively normal controls (CN) remains challenging under clinically realistic subject-disjoint evaluation. This study presents a compact 2D convolutional neural net…