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 proceedingConference contribution

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 languageEnglish
Title of host publication2014 IEEE 11th Consumer Communications and Networking Conference (CCNC)
PublisherIEEE
Number of pages4
ISBN (Print)9781479923557
DOIs
Publication statusPublished - Jan 2014
Externally publishedYes
Event2014 IEEE 11th Consumer Communications and Networking Conference - Las Vegas, United States
Duration: 10 Jan 201413 Jan 2014
Conference number: 11

Conference

Conference2014 IEEE 11th Consumer Communications and Networking Conference
Abbreviated titleCCNC
CountryUnited States
CityLas Vegas
Period10/01/1413/01/14

Fingerprint

Electroencephalography
Frequency bands
Synchronization

Cite this

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. https://doi.org/10.1109/CCNC.2014.6866646
Al-jumeily, Dhiya ; Iram, Shamaila ; Vialatte, Francois-benois ; Fergus, Paul. / A novel method to analyze EEG synchrony for the early diagnosis of Alzheimer's disease in optimized frequency bands. 2014 IEEE 11th Consumer Communications and Networking Conference (CCNC). IEEE, 2014.
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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.",
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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, 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; Fergus, Paul.

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Al-jumeily D, Iram S, Vialatte F, Fergus P. 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 https://doi.org/10.1109/CCNC.2014.6866646