A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands

Dhiya Al-jumeily; Shamaila Iram; Francois-benois Vialatte; Paul Fergus

doi:10.1109/CCNC.2014.6866646

A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Studies have reported that electroencephalogram (EEG) signals in Alzheimer’s disease (AD) patients usually have less synchronization as compared to healthy subjects. To detect this perturbation, three neural synchrony measurement techniques; phase synchrony, magnitudes squared coherence, and cross correlation are applied on a dataset for mild Alzheimer’s disease (MiAD) patients and healthy subjects. This paper discusses the use of principle component analysis (PCA) before applying neural synchrony measurement techniques and assesses the approach with others using the Mann-Whitney U test. The results show that applying PCA before synchrony measurement techniques improvements are made compared to the use of traditional techniques.

Original language	English
Title of host publication	2014 IEEE 11th Consumer Communications and Networking Conference (CCNC)
Publisher	IEEE
Number of pages	4
ISBN (Print)	9781479923557
DOIs	https://doi.org/10.1109/CCNC.2014.6866646
Publication status	Published - Jan 2014
Externally published	Yes
Event	2014 IEEE 11th Consumer Communications and Networking Conference - Las Vegas, United States Duration: 10 Jan 2014 → 13 Jan 2014 Conference number: 11

Conference

Conference	2014 IEEE 11th Consumer Communications and Networking Conference
Abbreviated title	CCNC
Country/Territory	United States
City	Las Vegas
Period	10/01/14 → 13/01/14

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http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=6866646Licence: Unspecified

Cite this

@inproceedings{37a8a4375e9d4123b5a7b20924fa27a1,

title = "A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands",

abstract = "Studies have reported that electroencephalogram (EEG) signals in Alzheimer{\textquoteright}s disease (AD) patients usually have less synchronization as compared to healthy subjects. To detect this perturbation, three neural synchrony measurement techniques; phase synchrony, magnitudes squared coherence, and cross correlation are applied on a dataset for mild Alzheimer{\textquoteright}s disease (MiAD) patients and healthy subjects. This paper discusses the use of principle component analysis (PCA) before applying neural synchrony measurement techniques and assesses the approach with others using the Mann-Whitney U test. The results show that applying PCA before synchrony measurement techniques improvements are made compared to the use of traditional techniques. ",

keywords = "Alzeimer's, early diagnosis, Electroencephalogram synchrony, principle component analysis",

author = "Dhiya Al-jumeily and Shamaila Iram and Francois-benois Vialatte and Paul Fergus",

year = "2014",

month = jan,

doi = "10.1109/CCNC.2014.6866646",

language = "English",

isbn = "9781479923557",

booktitle = "2014 IEEE 11th Consumer Communications and Networking Conference (CCNC)",

publisher = "IEEE",

address = "United States",

note = "2014 IEEE 11th Consumer Communications and Networking Conference, CCNC ; Conference date: 10-01-2014 Through 13-01-2014",

}

Al-jumeily, D, Iram, S, Vialatte, F & Fergus, P 2014, A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands. in 2014 IEEE 11th Consumer Communications and Networking Conference (CCNC). IEEE, 2014 IEEE 11th Consumer Communications and Networking Conference, Las Vegas, Nevada, United States, 10/01/14. https://doi.org/10.1109/CCNC.2014.6866646

A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands. / Al-jumeily, Dhiya; Iram, Shamaila; Vialatte, Francois-benois et al.

2014 IEEE 11th Consumer Communications and Networking Conference (CCNC). IEEE, 2014.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands

AU - Al-jumeily, Dhiya

AU - Iram, Shamaila

AU - Vialatte, Francois-benois

AU - Fergus, Paul

N1 - Conference code: 11

PY - 2014/1

Y1 - 2014/1

N2 - Studies have reported that electroencephalogram (EEG) signals in Alzheimer’s disease (AD) patients usually have less synchronization as compared to healthy subjects. To detect this perturbation, three neural synchrony measurement techniques; phase synchrony, magnitudes squared coherence, and cross correlation are applied on a dataset for mild Alzheimer’s disease (MiAD) patients and healthy subjects. This paper discusses the use of principle component analysis (PCA) before applying neural synchrony measurement techniques and assesses the approach with others using the Mann-Whitney U test. The results show that applying PCA before synchrony measurement techniques improvements are made compared to the use of traditional techniques.

AB - Studies have reported that electroencephalogram (EEG) signals in Alzheimer’s disease (AD) patients usually have less synchronization as compared to healthy subjects. To detect this perturbation, three neural synchrony measurement techniques; phase synchrony, magnitudes squared coherence, and cross correlation are applied on a dataset for mild Alzheimer’s disease (MiAD) patients and healthy subjects. This paper discusses the use of principle component analysis (PCA) before applying neural synchrony measurement techniques and assesses the approach with others using the Mann-Whitney U test. The results show that applying PCA before synchrony measurement techniques improvements are made compared to the use of traditional techniques.

KW - Alzeimer's

KW - early diagnosis

KW - Electroencephalogram synchrony

KW - principle component analysis

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DO - 10.1109/CCNC.2014.6866646

M3 - Conference contribution

SN - 9781479923557

BT - 2014 IEEE 11th Consumer Communications and Networking Conference (CCNC)

PB - IEEE

T2 - 2014 IEEE 11th Consumer Communications and Networking Conference

Y2 - 10 January 2014 through 13 January 2014

ER -

A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands

Abstract

Conference

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