TY - GEN
T1 - Electroencephalogram hybrid method for Alzheimer early detection
AU - Rodrigues, Pedro Miguel
AU - Freitas, Diamantino
AU - Teixeira, João Paulo
AU - Bispo, Bruno
AU - Alves, Dílio
AU - Garrett, Carolina
PY - 2018
Y1 - 2018
N2 - 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).
AB - 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).
KW - Alzheimer's diasease
KW - Cepstral analisys
KW - Cepstral distances
KW - Early diagnosis
KW - Electroencephalogram signals
KW - Wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=85061980451&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2018.10.030
DO - 10.1016/j.procs.2018.10.030
M3 - Conference contribution
AN - SCOPUS:85061980451
VL - 138
T3 - Procedia Computer Science
SP - 209
EP - 214
BT - International 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
A2 - Varajão, João Eduardo Quintela
A2 - Cruz-Cunha, Maria Manuela
A2 - Martinho, Ricardo
A2 - Rijo, Rui
A2 - Domingos, Dulce
A2 - Peres, Emanuel
PB - Elsevier
T2 - International 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
Y2 - 21 November 2018 through 23 November 2018
ER -