Gómez Carlos, Poza Jesús, Monge Jesús, Fernández Alberto, Hornero Roberto
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:702-5. doi: 10.1109/EMBC.2014.6943687.
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.
近似熵（ApEn）、样本熵（SampEn）和模糊熵（FuzzyEn）来检测阿尔茨海默病（AD）患者的脑磁图（MEG）背景活动。这三种方法用于测量时间序列的规律性。使用148通道全头磁强计对36例AD患者和24例老年对照受试者进行了5分钟的记录。我们的结果显示，AD患者的MEG活动比对照组更具规律性。此外，模糊熵显示两组之间存在统计学显著差异（p<0.01，Bonferroni校正的曼-惠特尼U检验），而近似熵和样本熵则没有。与其他熵算法相比，模糊熵具有更好的区分结果，这表明它在表征AD患者的MEG活动方面更有效。
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