Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA Convolutional Neural Network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings
Anno di pubblicazione2019
Formato-
Autore/iIeracitano, Cosimo; Mammone, Nadia; Bramanti, Alessia; Hussain, Amir; Morabito, Francesco C.
Affiliazioni autoriArray; Array; Array; Array
Autori CNR e affiliazioni
  • ALESSIA BRAMANTI
Lingua/e
  • inglese
AbstractA data-driven machine deep learning approach is proposed for differentiating subjects with Alzheimer's Disease (AD), Mild Cognitive Impairment (MCI) and Healthy Control (HC), by only analyzing noninvasive scalp EEG recordings. The methodology here proposed consists of evaluating the power spectral density (PSD) of the 19-channels EEG traces and representing the related spectral profiles into 2-d gray scale images (PSD-images). A customized Convolutional Neural Network with one processing module of convolution, Rectified Linear Units (ReLu) and pooling layer (CNN1) is designed to extract from PSD-images some suitable features and to perform the corresponding two and three-ways classification tasks. The resulting CNN is shown to provide better classification performance when compared to more conventional learning machines; indeed, it achieves an average accuracy of 89.8% in binary classification and of 83.3% in three-ways classification. These results encourage the use of deep processing systems (here, an engineered first stage, namely the PSD-image extraction, and a second or multiple CNN stage) in challenging clinical frameworks. Crown Copyright (C) 2018 Published by Elsevier B.V. All rights reserved.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da96
Pagine a107
Pagine totali12
RivistaNeurocomputing (Amst.)
Attiva dal 1989
Editore: Elsevier Science Publishers - Amsterdam
Paese di pubblicazione: Paesi Bassi
Lingua: inglese
ISSN: 0925-2312
Titolo chiave: Neurocomputing (Amst.)
Titolo proprio: Neurocomputing. (Amst.)
Titolo abbreviato: Neurocomputing (Amst.)
Numero volume della rivista323
Fascicolo della rivista-
DOI10.1016/j.neucom.2018.09.071
Verificato da referee-
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • ISI Web of Science (WOS) (Codice:000448945600008)
Parole chiaveDeep learning, Convolutional Neural Network, Power spectral density, Alzheimer's disease, Mild Cognitive Impairment
Link (URL, URI)-
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • ISASI — Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello"
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
Allegati