[HTML][HTML] International Federation of Clinical Neurophysiology (IFCN)–EEG research workgroup: Recommendations on frequency and topographic analysis of resting …

C Babiloni, RJ Barry, E Başar, KJ Blinowska… - Clinical …, 2020 - Elsevier
Abstract In 1999, the International Federation of Clinical Neurophysiology (IFCN) published
“IFCN Guidelines for topographic and frequency analysis of EEGs and EPs”(Nuwer et al …

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 …

A convolutional neural network approach for classification of dementia stages based on 2D-spectral representation of EEG recordings

C Ieracitano, N Mammone, A Bramanti, A Hussain… - Neurocomputing, 2019 - Elsevier
A 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 …

Efficient deep neural networks for classification of Alzheimer's disease and mild cognitive impairment from scalp EEG recordings

S Fouladi, AA Safaei, N Mammone, F Ghaderi… - Cognitive …, 2022 - Springer
The early diagnosis of subjects with mild cognitive impairment (MCI) is an effective
appliance of prognosis of Alzheimer's disease (AD). Electroencephalogram (EEG) has many …

Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms

C Babiloni, R Lizio, N Marzano, P Capotosto… - International Journal of …, 2016 - Elsevier
Alzheimer's disease (AD) is the most common type of neurodegenerative disorder, typically
causing dementia along aging. AD is mainly characterized by a pathological extracellular …

[HTML][HTML] Review on solving the inverse problem in EEG source analysis

R Grech, T Cassar, J Muscat, KP Camilleri… - … of neuroengineering and …, 2008 - Springer
In this primer, we give a review of the inverse problem for EEG source localization. This is
intended for the researchers new in the field to get insight in the state-of-the-art techniques …

Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: recommendations of an expert panel

C Babiloni, X Arakaki, H Azami, K Bennys… - Alzheimer's & …, 2021 - Wiley Online Library
Abstract The Electrophysiology Professional Interest Area (EPIA) and Global Brain
Consortium endorsed recommendations on candidate electroencephalography (EEG) …

EEG dynamics in patients with Alzheimer's disease

J Jeong - Clinical neurophysiology, 2004 - Elsevier
Alzheimer's disease (AD) is the most common neurodegenerative disorder characterized by
cognitive and intellectual deficits and behavior disturbance. The electroencephalogram …

EEG source imaging

CM Michel, MM Murray, G Lantz, S Gonzalez… - Clinical …, 2004 - Elsevier
Objective: Electroencephalography (EEG) is an important tool for studying the temporal
dynamics of the human brain's large-scale neuronal circuits. However, most EEG …

EEG and ERP biomarkers of Alzheimer's disease: a critical review.

A Horvath, A Szucs, G Csukly, A Sakovics… - Frontiers in bioscience …, 2018 - real.mtak.hu
Here we critically review studies that used electroencephalography (EEG) or event-related
potential (ERP) indices as a biomarker of Alzheimer's disease. In the first part we overview …