A review on transfer learning in EEG signal analysis

Z Wan, R Yang, M Huang, N Zeng, X Liu - Neurocomputing, 2021 - Elsevier
Electroencephalogram (EEG) signal analysis, which is widely used for human-computer
interaction and neurological disease diagnosis, requires a large amount of labeled data for …

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 …

Connectivity analysis in EEG data: a tutorial review of the state of the art and emerging trends

G Chiarion, L Sparacino, Y Antonacci, L Faes, L Mesin - Bioengineering, 2023 - mdpi.com
Understanding how different areas of the human brain communicate with each other is a
crucial issue in neuroscience. The concepts of structural, functional and effective …

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) …

Gains in cognition through combined cognitive and physical training: the role of training dosage and severity of neurocognitive disorder

PD Bamidis, P Fissler, SG Papageorgiou… - Frontiers in aging …, 2015 - frontiersin.org
Physical as well as cognitive training interventions improve specific cognitive functions but
effects barely generalize on global cognition. Combined physical and cognitive training may …

Single slice based detection for Alzheimer's disease via wavelet entropy and multilayer perceptron trained by biogeography-based optimization

SH Wang, Y Zhang, YJ Li, WJ Jia, FY Liu… - Multimedia Tools and …, 2018 - Springer
Detection of Alzheimer's disease (AD) from magnetic resonance images can help
neuroradiologists to make decision rapidly and avoid missing slight lesions in the brain …

Design, implementation, and wide pilot deployment of FitForAll: an easy to use exergaming platform improving physical fitness and life quality of senior citizens

EI Konstantinidis, AS Billis… - IEEE journal of …, 2014 - ieeexplore.ieee.org
Many platforms have emerged as response to the call for technology supporting active and
healthy aging. Key requirements for any such e-health systems and any subsequent …

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 …

Impact of the reference choice on scalp EEG connectivity estimation

F Chella, V Pizzella, F Zappasodi… - Journal of neural …, 2016 - iopscience.iop.org
Objective. Several scalp EEG functional connectivity studies, mostly clinical, seem to
overlook the reference electrode impact. The subsequent interpretation of brain connectivity …

Detection of pathological brain in MRI scanning based on wavelet-entropy and naive Bayes classifier

X Zhou, S Wang, W Xu, G Ji, P Phillips, P Sun… - … , IWBBIO 2015, Granada …, 2015 - Springer
An accurate diagnosis is important for the medical treatment of patients suffered from brain
disease. Nuclear magnetic resonance images are commonly used by technicians to assist …