Systematic review on resting‐state EEG for Alzheimer's disease diagnosis and progression assessment

R Cassani, M Estarellas, R San-Martin… - Disease …, 2018‏ - Wiley Online Library
Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of
the more than 46 million dementia cases estimated worldwide. Although there is no cure for …

Methods for artifact detection and removal from scalp EEG: A review

MK Islam, A Rastegarnia, Z Yang - Neurophysiologie Clinique/Clinical …, 2016‏ - Elsevier
Electroencephalography (EEG) is the most popular brain activity recording technique used
in wide range of applications. One of the commonly faced problems in EEG recordings is the …

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 …

Opportunities and methodological challenges in EEG and MEG resting state functional brain network research

E Van Diessen, T Numan, E Van Dellen… - Clinical …, 2015‏ - Elsevier
Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting
state are increasingly used to study functional connectivity and network topology. Moreover …

Identification and removal of physiological artifacts from electroencephalogram signals: A review

MMN Mannan, MA Kamran, MY Jeong - Ieee Access, 2018‏ - ieeexplore.ieee.org
Electroencephalogram (EEG), boasting the advantages of portability, low cost, and
hightemporal resolution, is a non-invasive brain-imaging modality that can be used to …

Ocular artifact elimination from electroencephalography signals: A systematic review

R Ranjan, BC Sahana, AK Bhandari - Biocybernetics and Biomedical …, 2021‏ - Elsevier
Electroencephalography (EEG) is the signal of intrigue that has immense application in the
clinical diagnosis of various neurological, psychiatric, psychological, psychophysiological …

Exploring rhythms and channels-based EEG biomarkers for early detection of alzheimer's disease

S Siuly, ÖF Alçin, H Wang, Y Li… - IEEE Transactions on …, 2024‏ - ieeexplore.ieee.org
There is no treatment that permanently cures Alzheimer's disease (AD); however, early
detection can alleviate the severe effects of the disease. To support early detection of the …

Machine learning algorithms and statistical approaches for Alzheimer's disease analysis based on resting-state EEG recordings: A systematic review

KD Tzimourta, V Christou, AT Tzallas… - … journal of neural …, 2021‏ - World Scientific
Alzheimer's Disease (AD) is a neurodegenerative disorder and the most common type of
dementia with a great prevalence in western countries. The diagnosis of AD and its …

Using CNN Saliency Maps and EEG Modulation Spectra for Improved and More Interpretable Machine Learning‐Based Alzheimer's Disease Diagnosis

M Lopes, R Cassani, TH Falk - Computational Intelligence and …, 2023‏ - Wiley Online Library
Biomarkers based on resting‐state electroencephalography (EEG) signals have emerged as
a promising tool in the study of Alzheimer's disease (AD). Recently, a state‐of‐the‐art …

Extracting salient features for EEG-based diagnosis of Alzheimer's disease using support vector machine classifier

NN Kulkarni, VK Bairagi - IETE Journal of Research, 2017‏ - Taylor & Francis
Alzheimer's disease (AD) is one of the most common and fastest growing
neurodegenerative diseases in the western countries. Development of different biomarkers …