Electroencephalogram hybrid method for Alzheimer early detection

Pedro Miguel Rodrigues*, Diamantino Freitas, João Paulo Teixeira, Bruno Bispo, Dílio Alves, Carolina Garrett

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Citations (Scopus)
17 Downloads

Abstract

Alzheimer's disease (AD) is a neurocognitive illness that leads to dementia and mainly affects the elderly. As the percentage of old people is strongly increasing worldwide, it is urgent to develop contributions to solve this complex problem. The early diagnosis at AD first stage known as Mild Cognitive Impairment (MCI) needs a better accuracy and there is not a biomarker able to detect AD without invasive tests. In this study, Electroencephalogram (EEG) signals have been used to serve as a way of finding parameters to improve AD diagnosis in first stages. For that, a hybrid method based on a Cepstral analysis of EEG Discrete Wavelet Transform (DWT) multiband decomposition was developed. Several Cepstral Distances (CD) were extracted to verify the lag between cepstra of conventional bands signals. The results showed that this hybrid method is a good tool for describing and distinguishing the AD EEG activity along its different stages because several statistically significant parameters variations were found between controls, MCI, moderate AD and advanced AD (the lowest p-value=0.003<0.05).
Original languageEnglish
Title of host publicationInternational Conference on ENTERprise Information Systems / International Conference on Project MANagement / International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2018
EditorsJoão Eduardo Quintela Varajão, Maria Manuela Cruz-Cunha, Ricardo Martinho, Rui Rijo, Dulce Domingos, Emanuel Peres
PublisherElsevier
Pages209-214
Number of pages6
Volume138
DOIs
Publication statusPublished - 2018
EventInternational Conference on ENTERprise Information Systems / International Conference on Project MANagement / International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2018 - Lisbon, Portugal
Duration: 21 Nov 201823 Nov 2018

Publication series

NameProcedia Computer Science
PublisherElsevier BV

Conference

ConferenceInternational Conference on ENTERprise Information Systems / International Conference on Project MANagement / International Conference on Health and Social Care Information Systems and Technologies, CENTERIS/ProjMAN/HCist 2018
Country/TerritoryPortugal
CityLisbon
Period21/11/1823/11/18

Keywords

  • Alzheimer's diasease
  • Cepstral analisys
  • Cepstral distances
  • Early diagnosis
  • Electroencephalogram signals
  • Wavelet transform

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