Early diagnosis of Alzheimer's disease: the role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts

PM Rossini, R Di Iorio, F Vecchio, M Anfossi… - Clinical …, 2020 - Elsevier
Alzheimer's disease (AD) is the most common neurodegenerative disease among the
elderly with a progressive decline in cognitive function significantly affecting quality of life …

Diagnosis of Alzheimer's disease from EEG signals: where are we standing?

J Dauwels, F Vialatte, A Cichocki - Current Alzheimer Research, 2010 - ingentaconnect.com
This paper reviews recent progress in the diagnosis of Alzheimer's disease (AD) from
electroencephalograms (EEG). Three major effects of AD on EEG have been observed …

Complexity analysis of EEG, MEG, and fMRI in mild cognitive impairment and Alzheimer's disease: a review

J Sun, B Wang, Y Niu, Y Tan, C Fan, N Zhang, J Xue… - Entropy, 2020 - mdpi.com
Alzheimer's disease (AD) is a degenerative brain disease with a high and irreversible
incidence. In recent years, because brain signals have complex nonlinear dynamics, there …

Automated multiclass classification of spontaneous EEG activity in Alzheimer's disease and mild cognitive impairment

SJ Ruiz-Gómez, C Gómez, J Poza, GC Gutiérrez-Tobal… - Entropy, 2018 - mdpi.com
The discrimination of early Alzheimer's disease (AD) and its prodromal form (ie, mild
cognitive impairment, MCI) from cognitively healthy control (HC) subjects is crucial since the …

How machine learning is powering neuroimaging to improve brain health

NM Singh, JB Harrod, S Subramanian, M Robinson… - Neuroinformatics, 2022 - Springer
This report presents an overview of how machine learning is rapidly advancing clinical
translational imaging in ways that will aid in the early detection, prediction, and treatment of …

[PDF][PDF] Brain computer interface: EEG signal preprocessing issues and solutions

N Elsayed, ZS Zaghloul, M Bayoumi - Int. J. Comput. Appl, 2017 - e-tarjome.com
ABSTRACT Brain Computer Interface (BCI) is often directed at mapping, assisting, or
repairing human cognitive or sensory-motor functions. Electroencephalogram (EEG) is a …

Automatic diagnosis of mild cognitive impairment using electroencephalogram spectral features

M Kashefpoor, H Rabbani… - Journal of Medical Signals …, 2016 - journals.lww.com
Alzheimer's disease (AD) is one of the most expensive and fatal diseases in the elderly
population. Up to now, no cure have been found for AD, so early stage diagnosis is the only …

Dynamic neural network architecture inspired by the immune algorithm to predict preterm deliveries in pregnant women

AJ Hussain, P Fergus, H Al-Askar, D Al-Jumeily… - Neurocomputing, 2015 - Elsevier
There has been some improvement in the treatment of preterm infants, which has helped to
increase their chance of survival. However, the rate of premature births is still globally …

Multiway array decomposition analysis of EEGs in Alzheimer's disease

CFV Latchoumane, FB Vialatte, J Solé-Casals… - Journal of neuroscience …, 2012 - Elsevier
Methods for the extraction of features from physiological datasets are growing needs as
clinical investigations of Alzheimer's disease (AD) in large and heterogeneous population …

Supervised dictionary learning of EEG signals for mild cognitive impairment diagnosis

M Kashefpoor, H Rabbani, M Barekatain - Biomedical Signal Processing …, 2019 - Elsevier
Abstract Mild Cognitive Impairment (MCI) is an intermediate stage of memory decline
between normal aging and Alzheimer's disease or other types of dementia. MCI diagnosis is …