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Updated: Jun 28, 2026
Examining the Characteristics of Episodic Memory using Event-related Potentials in Patients with Alzheimer's Disease
Published on: August 30, 2011
Nonlinear analysis of electroencephalogram and magnetoencephalogram recordings in patients with Alzheimer's disease
Roberto Hornero1, Daniel Abásolo, Javier Escudero
1Biomedical Engineering Group, E.T.S.I. Telecomunicación, University of Valladolid, Camino del Cementerio s/n, 47011 Valladolid, Spain. robhor@tel.uva.es
Abstract:
The aim of the present study is to show the usefulness of nonlinear methods to analyse the electroencephalogram (EEG) and magnetoencephalogram (MEG) in patients with Alzheimer's disease (AD). The following nonlinear methods have been applied to study the EEG and MEG background activity in AD patients and control subjects: approximate entropy, sample entropy, multiscale entropy, auto-mutual information and Lempel-Ziv complexity. We discuss why these nonlinear methods are appropriate to analyse the EEG and MEG. Furthermore, the performance of all these methods has been compared when applied to the same databases of EEG and MEG recordings. Our results show that EEG and MEG background activities in AD patients are less complex and more regular than in healthy control subjects. In line with previous studies, our work suggests that nonlinear analysis techniques could be useful in AD diagnosis.
