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Evaluation of EEG spectralfeatures in Alzheimer disease discrimination

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Detalhes bibliográficos
Resumo: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.
Autores principais:Rodrigues, Pedro Miguel
Outros Autores:Bispo, Bruno; Freitas, Diamantino Silva; Teixeira, João Paulo; Carreres, Alicia
Assunto:Alzheimer’s disease Elderly people Diagnose Electroencephalogram
Ano:2013
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo: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.