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Analysis of spontaneous MEG activity in patients with Alzheimer's disease using spectral entropies.

Poza, J, Hornero, R, Abásolo, D, Fernández, A and Escudero, J (2007) Analysis of spontaneous MEG activity in patients with Alzheimer's disease using spectral entropies.

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Abstract

The aim of this study was to explore the ability of several spectral entropies to discriminate between spontaneous magnetoencephalographic (MEG) oscillations from 20 Alzheimer's disease (AD) patients and 21 controls. Hence, the relative spectral power (RSP) in classical frequency bands was calculated from the averaged power spectral density. Given the fact that the RSP can be viewed as a probability distribution function, the Shannon spectral entropy, Tsallis spectral entropy, generalized escort-Tsallis spectral entropy and Rényi spectral entropy were calculated from the RSP. Significant differences for each parameter were assessed with Mann-Whitney U test, whereas classification performance was studied using binary logistic regression. Results revealed an increase in the RSP of control subjects at beta and gamma bands, while AD patients showed an increase in the RSP values at delta and theta bands. Entropies obtained statistically significant lower values for AD patients than for controls. This issue suggests a significant decrease in irregularity of AD patients' MEG activity.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Copyright 2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords: Aged, Algorithms, Alzheimer Disease, Artificial Intelligence, Brain, Diagnosis, Computer-Assisted, Entropy, Female, Humans, Magnetoencephalography, Male, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity
Divisions: Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Depositing User: Symplectic Elements
Date Deposited: 14 Nov 2012 11:52
Last Modified: 23 Sep 2013 19:36
URI: http://epubs.surrey.ac.uk/id/eprint/713575

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