A Novel Method of Early Diagnosis of Alzheimer’s Disease Based on EEG Signals

Dhiya Al-jumeily, Shamaila Iram, Francois-benois Vialatte, Paul Fergus, Abir Hussain

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Studies have reported that electroencephalogram signals in Alzheimer’s disease patients usually have less synchronization than those of healthy subjects. Changes in electroencephalogram signals start at early stage but, clinically, these changes are not easily detected. To detect this perturbation, three neural synchrony measurement techniques: phase synchrony, magnitude squared coherence, and cross correlation are applied to three different databases of mild Alzheimer’s disease patients and healthy subjects. We have compared the right and left temporal lobes of the brain with the rest of the brain areas (frontal, central, and occipital) as temporal regions are relatively the first ones to be affected by Alzheimer’s disease. Moreover, electroencephalogram signals are further classified into five different frequency bands (delta, theta, alpha beta, and gamma) because each frequency band has its own physiological significance in terms of signal evaluation. A new approach using principal component analysis before applying neural synchrony measurement techniques has been presented and compared with Average technique. The simulation results indicated that applying principal component analysis before synchrony measurement techniques shows significantly better results as compared to the lateral one. At the end, all the aforementioned techniques are assessed by a statistical test (Mann-Whitney U test) to compare the results.
LanguageEnglish
Number of pages11
JournalThe Scientific World Journal
Volume2015
DOIs
Publication statusPublished - 2015
Externally publishedYes

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synchrony
Electroencephalography
Early Diagnosis
Alzheimer Disease
Temporal Lobe
Principal Component Analysis
Principal component analysis
Frequency bands
Brain
Healthy Volunteers
brain
principal component analysis
Statistical tests
Nonparametric Statistics
Synchronization
Databases
perturbation
method
simulation
test

Cite this

Al-jumeily, Dhiya ; Iram, Shamaila ; Vialatte, Francois-benois ; Fergus, Paul ; Hussain, Abir. / A Novel Method of Early Diagnosis of Alzheimer’s Disease Based on EEG Signals. In: The Scientific World Journal. 2015 ; Vol. 2015.
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A Novel Method of Early Diagnosis of Alzheimer’s Disease Based on EEG Signals. / Al-jumeily, Dhiya; Iram, Shamaila; Vialatte, Francois-benois; Fergus, Paul; Hussain, Abir.

In: The Scientific World Journal, Vol. 2015, 2015.

Research output: Contribution to journalArticle

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