title: A novel method of early diagnosis of Alzheimer's disease based on EEG signals.
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.
authors: Applied Computing Research Group, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK.
authors: Dhiya
authors: 0000-0002-9170-0568
authors: D
authors: Al-Jumeily
authors: Applied Computing Research Group, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK.
authors: Shamaila
authors: S
authors: Iram
authors: Laboratoire SIGMA, ESPCI ParisTech, 14 boulevard des Frères Voisin, 92130 Issy-les-Moulineaux, France.
authors: Francois-Benois
authors: FB
authors: Vialatte
authors: Applied Computing Research Group, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK.
authors: Paul
authors: 0000-0002-7070-4447
authors: P
authors: Fergus
authors: Applied Computing Research Group, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK.
authors: Abir
authors: 0000-0001-8413-0045
authors: A
authors: Hussain
mesh_terms: D000544:Alzheimer Disease / Q000175:diagnosis*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D058407:Electroencephalography Phase Synchronization / Q000502:physiology*; D006801:Humans; D025341:Principal Component Analysis; D018709:Statistics, Nonparametric; D013702:Temporal Lobe / Q000502:physiology*