Abstract
The aim of this study was to examine the magnetoencephalography (MEG) background activity in Alzheimer's disease (AD) using three embedding entropies: approximate entropy (ApEn), sample entropy (SampEn), and fuzzy entropy (FuzzyEn). These three methods measure the time series regularity. Five minutes of recording were acquired with a 148-channel whole-head magnetometer from 36 AD patients and 24 elderly control subjects. Our results showed that MEG activity was more regular in AD patients than in controls. Additionally, FuzzyEn revealed statistically significant differences between the two groups (p <; 0.01, Bonferroni-corrected Mann-Whitney U-test), while ApEn and SampEn did not. The better discriminating results of FuzzyEn in comparison with the other entropy algorithms suggest that it is more efficient for the characterization of MEG activity in AD.
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