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Distance-based Lempel-Ziv Complexity for the Analysis of Electroencephalograms in Patients with Alzheimer's Disease

Simons, Samantha and Abasolo, Daniel Emilio (2017) Distance-based Lempel-Ziv Complexity for the Analysis of Electroencephalograms in Patients with Alzheimer's Disease Entropy An International and Interdisciplinary Journal of Entropy and Information Studies, 19 (3), 129.

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Abstract

The analysis of electroencephalograms (EEGs) of patients with Alzheimer’s disease (AD) could contribute to the diagnosis of this dementia. In this study, a new non-linear signal processing metric, distance-based Lempel-Ziv complexity (dLZC), is introduced to characterise changes between pairs of electrodes in EEGs in AD. When complexity in each signal arises from different sub-sequences dLZC would be greater than when similar sub-sequences are present in each signal. EEGs from 11 AD patients and 11 age-matched control subjects were analysed. The dLZC values for AD patients were lower than for control subjects for most electrode pairs, with statistically significant differences (p<0.01, Student’s t-test) in 17 electrode pairs in the distant left, local posterior left, and interhemispheric regions. Maximum diagnostic accuracies with leave-one-out cross-validation were 77.27% for subject-based classification and 78.25% for epoch-based classification. These findings suggest not only that EEGs from AD patients are less complex than those from controls, but also that the richness of the information contained in pairs of EEGs from patients is also lower than in age-matched controls. The analysis of EEGs in AD with dLZC may increase the insight into brain dysfunction providing complementary information to that obtained with other complexity and synchrony methods.

Item Type: Article
Subjects : Mechanical Engineering Science
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
NameEmailORCID
Simons, Samanthas.simons@surrey.ac.ukUNSPECIFIED
Abasolo, Daniel EmilioD.Abasolo@surrey.ac.ukUNSPECIFIED
Date : 17 March 2017
Identification Number : 10.3390/e19030129
Copyright Disclaimer : This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
Uncontrolled Keywords : Alzheimer’s Disease; Electroencephalogram; Non-linear Analysis; Lempel-Ziv Complexity; Distance-based Lempel-Ziv Complexity
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 15 Mar 2017 18:12
Last Modified : 19 Jul 2017 13:09
URI: http://epubs.surrey.ac.uk/id/eprint/813787

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