Evaluation of EEG spectral features in alzheimer disease discrimination

P. M. Rodrigues; B. C. Bispo; Diamantino Freitas; João Paulo Teixeira; A. Carreres

Evaluation of EEG spectral features in alzheimer disease discrimination

P. M. Rodrigues, B. C. Bispo, Diamantino Freitas, João Paulo Teixeira, A. Carreres

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

Abstract

Alzheimer's disease (AD) is considered one of the most disabling diseases and it has a high prevalence in developed countries. It is as well the most common cause of dementia and it affects particularly the elderly. The current AD diagnosis accuracy is relatively low. It is therefore necessary to optimize the methods for AD detection. The electroencephalogram (EEG) is an inexpensive and noninvasive technique, that is able to record the electromagnetic fields produced by the brain activity. It has shown in the recent past a growing quality of the contribution to show brain disorders. The aim of this study was to evaluate the individual and combined power of several EEG features in AD discrimination. 95.00% of sensitivity, 100.00% of specificity, 97.06% of accuracy and 0.98 of AUC were the best classification results obtained in this work.

Original language	English
Title of host publication	21st European Signal Processing Conference (EUSIPCO 2013)
Publisher	IEEE Canada
Pages	1-5
Number of pages	5
ISBN (Print)	9780992862602
Publication status	Published - 2013
Externally published	Yes
Event	21st European Signal Processing Conference - Marrakech, Morocco Duration: 9 Sept 2013 → 13 Sept 2013

Conference

Conference	21st European Signal Processing Conference
Abbreviated title	EUSIPCO 2013
Country/Territory	Morocco
City	Marrakech
Period	9/09/13 → 13/09/13

Cite this

@inproceedings{39f0a13082254ebabc7754099e291aa6,

title = "Evaluation of EEG spectral features in alzheimer disease discrimination",

abstract = "Alzheimer's disease (AD) is considered one of the most disabling diseases and it has a high prevalence in developed countries. It is as well the most common cause of dementia and it affects particularly the elderly. The current AD diagnosis accuracy is relatively low. It is therefore necessary to optimize the methods for AD detection. The electroencephalogram (EEG) is an inexpensive and noninvasive technique, that is able to record the electromagnetic fields produced by the brain activity. It has shown in the recent past a growing quality of the contribution to show brain disorders. The aim of this study was to evaluate the individual and combined power of several EEG features in AD discrimination. 95.00% of sensitivity, 100.00% of specificity, 97.06% of accuracy and 0.98 of AUC were the best classification results obtained in this work.",

author = "Rodrigues, {P. M.} and Bispo, {B. C.} and Diamantino Freitas and Teixeira, {Jo{\~a}o Paulo} and A. Carreres",

year = "2013",

language = "English",

isbn = "9780992862602",

pages = "1--5",

booktitle = "21st European Signal Processing Conference (EUSIPCO 2013)",

publisher = "IEEE Canada",

address = "Canada",

note = "21st European Signal Processing Conference, EUSIPCO 2013 ; Conference date: 09-09-2013 Through 13-09-2013",

}

TY - GEN

T1 - Evaluation of EEG spectral features in alzheimer disease discrimination

AU - Rodrigues, P. M.

AU - Bispo, B. C.

AU - Freitas, Diamantino

AU - Teixeira, João Paulo

AU - Carreres, A.

PY - 2013

Y1 - 2013

N2 - Alzheimer's disease (AD) is considered one of the most disabling diseases and it has a high prevalence in developed countries. It is as well the most common cause of dementia and it affects particularly the elderly. The current AD diagnosis accuracy is relatively low. It is therefore necessary to optimize the methods for AD detection. The electroencephalogram (EEG) is an inexpensive and noninvasive technique, that is able to record the electromagnetic fields produced by the brain activity. It has shown in the recent past a growing quality of the contribution to show brain disorders. The aim of this study was to evaluate the individual and combined power of several EEG features in AD discrimination. 95.00% of sensitivity, 100.00% of specificity, 97.06% of accuracy and 0.98 of AUC were the best classification results obtained in this work.

AB - Alzheimer's disease (AD) is considered one of the most disabling diseases and it has a high prevalence in developed countries. It is as well the most common cause of dementia and it affects particularly the elderly. The current AD diagnosis accuracy is relatively low. It is therefore necessary to optimize the methods for AD detection. The electroencephalogram (EEG) is an inexpensive and noninvasive technique, that is able to record the electromagnetic fields produced by the brain activity. It has shown in the recent past a growing quality of the contribution to show brain disorders. The aim of this study was to evaluate the individual and combined power of several EEG features in AD discrimination. 95.00% of sensitivity, 100.00% of specificity, 97.06% of accuracy and 0.98 of AUC were the best classification results obtained in this work.

M3 - Conference contribution

SN - 9780992862602

SP - 1

EP - 5

BT - 21st European Signal Processing Conference (EUSIPCO 2013)

PB - IEEE Canada

T2 - 21st European Signal Processing Conference

Y2 - 9 September 2013 through 13 September 2013

ER -

Evaluation of EEG spectral features in alzheimer disease discrimination

Abstract

Conference

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