Multi-Scale Probabilistic Score Fusion for Enhancing Alzheimer’s Disease Detection Using EEG

Maxime Bedoin, Bernadette Dorizzi, Jérôme Boudy, Kiyoka Kinugawa, Nesma Houmani

2025

Abstract

In this work, we propose a fusion approach to analyze EEG signals for the discrimination between patients with Subjective Cognitive Impairment (SCI) and patients suffering from Alzheimer’s Disease (AD). In this framework, we analyze EEG signals at different epoch durations, following a multi-scale procedure, and in different frequency bands, using Phase-Lag Index (PLI) and Dynamic Time Warping (DTW) for functional connectivity measurement. Experiments show that our fusion approach leads to an improvement of classification results, reaching an AUC of 0.902 with PLI, and 0.894 with DTW; whereas we obtain an AUC of 0.845 with PLI and 0.801 with DTW when computing connectivity on the entire signal, as usually done in the literature. Furthermore, with the additional fusion of the scores obtained at different frequency bands, we reach the best performance with both PLI (AUC=0.95, Accuracy=91%) and DTW (AUC=0.98, Accuracy=95%). Finally, we investigate the generalization capability of our proposal on a test set. We found that our fusion scheme allows obtaining better classification results comparatively to when we consider the entire signal to compute functional connectivity.

Paper Citation

in Harvard Style

Bedoin M., Dorizzi B., Boudy J., Kinugawa K. and Houmani N. (2025). Multi-Scale Probabilistic Score Fusion for Enhancing Alzheimer’s Disease Detection Using EEG. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS; ISBN 978-989-758-731-3, SciTePress, pages 741-751. DOI: 10.5220/0013169700003911

in Bibtex Style

@conference{biosignals25,
author={Maxime Bedoin and Bernadette Dorizzi and Jérôme Boudy and Kiyoka Kinugawa and Nesma Houmani},
title={Multi-Scale Probabilistic Score Fusion for Enhancing Alzheimer’s Disease Detection Using EEG},
booktitle={Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS},
year={2025},
pages={741-751},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013169700003911},
isbn={978-989-758-731-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSIGNALS
TI - Multi-Scale Probabilistic Score Fusion for Enhancing Alzheimer’s Disease Detection Using EEG
SN - 978-989-758-731-3
AU - Bedoin M.
AU - Dorizzi B.
AU - Boudy J.
AU - Kinugawa K.
AU - Houmani N.
PY - 2025
SP - 741
EP - 751
DO - 10.5220/0013169700003911
PB - SciTePress