Objective: Alzheimer's Disease (AD) is the most common form of dementia, for which actually no cure is known. Different studies have shown that AD has (at least) three major effects on Electroencephalography (EEG) signals: enhanced complexity, slowing of signals, and perturbations in EEG synchrony. The aim of this work is to achieve an automatic patients classification from EEG biomedical signals involved in AD and Mild Cognitive Impairment (MCI) in order to support physicians in a more correct individual diagnosis.

Alzheimer’s disease patients classification by using EEG signals processing / De Cola, M. C.; Fiscon, Giulia; E., Weitschek; S., De Salvo; G., Felici; P., Bramanti. - ELETTRONICO. - 1:(2014), pp. 196-196. (Intervento presentato al convegno Società italiana di neurologia: SIN. XLV CONGRESSO NAZIONALE tenutosi a Cagliari nel 11-14 OTTOBRE 2014).

Alzheimer’s disease patients classification by using EEG signals processing

FISCON, GIULIA;
2014

Abstract

Objective: Alzheimer's Disease (AD) is the most common form of dementia, for which actually no cure is known. Different studies have shown that AD has (at least) three major effects on Electroencephalography (EEG) signals: enhanced complexity, slowing of signals, and perturbations in EEG synchrony. The aim of this work is to achieve an automatic patients classification from EEG biomedical signals involved in AD and Mild Cognitive Impairment (MCI) in order to support physicians in a more correct individual diagnosis.
2014
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/740613
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