Amplitude-and Fluctuation-Based Dispersion Entropy for the Analysis of Resting-State Magnetoencephalogram Irregularity in MCI and Alzheimer's Disease Patients

Hamed Azami, Javier Escudero, Alberto Fernandez, Stephen Arnold

Research output: Contribution to conferencePosterpeer-review

Abstract

Alzheimer's Disease (AD) affects brain activity. Some of these changes may be reflected in magnetoencephalography (MEG) recordings. Since MEGs are considered as the outputs of a nonlinear system (i.e., the brain), nonlinear methods, such as entropy, have been widely used for their analysis. Entropy shows the amount of information or uncertainty of signals. Because of neuronal death, a general effect of lack of neurotransmitter, and loss of connectivity of local neural networks in AD or mild cognitive impairment (MCI), an entropy decrease in MEG signals for AD or MCI patients may be expected. Thus, we evaluate our introduced dispersion entropy (DispEn) and fluctuation‐based DispEn (FDispEn) in the characterization of MEGs for MCI and AD patients vs. controls
Original languageEnglish
DOIs
Publication statusPublished - 1 Jul 2019
EventAlzheimer's Association International Conference - Los Angeles, United States
Duration: 14 Jul 201918 Jul 2019

Conference

ConferenceAlzheimer's Association International Conference
Abbreviated titleAAIC19
Country/TerritoryUnited States
CityLos Angeles
Period14/07/1918/07/19

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