EEG Biomarkers for Alzheimer's Disease: A Novel Automated Pipeline for Detecting and Monitoring Disease Progression
Our findings suggest that this automated approach provides a promising initial framework for implementing EEG biomarkers in the AD patient population, paving the way for improved diagnostic and monitoring strategies.
Authors
- Leif Simmatis (ORCID: https://orcid.org/0000-0002-1234-5335)
- Emma E. Russo (ORCID: https://orcid.org/0009-0006-1102-8553)
- Irene E. Harmsen (ORCID: https://orcid.org/0000-0001-9056-1706)
- Nicole Samuel (ORCID: https://orcid.org/0000-0002-4844-3404)
- Donghun Oh (ORCID: https://orcid.org/0000-0003-3824-4783)
- E. X. Chen
- Queenny Chiu (ORCID: https://orcid.org/0009-0008-4425-165X)
- Tayo Steininger
- Porsha Taheri
- Haleigh Riddell
- Michelle Lin
Institutions
- University of Toronto (CA)
- Institut des Sciences Cognitives Marc Jeannerod (FR)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_096963
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00