Systematic review on resting‐state EEG for Alzheimer's disease diagnosis and progression assessment
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 …
the more than 46 million dementia cases estimated worldwide. Although there is no cure for …
EEG signal processing and supervised machine learning to early diagnose Alzheimer's disease
D Pirrone, E Weitschek, P Di Paolo, S De Salvo… - Applied sciences, 2022 - mdpi.com
Electroencephalography (EEG) signal analysis is a fast, inexpensive, and accessible
technique to detect the early stages of dementia, such as Mild Cognitive Impairment (MCI) …
technique to detect the early stages of dementia, such as Mild Cognitive Impairment (MCI) …
Driver sleepiness detection from EEG and EOG signals using GAN and LSTM networks
Y Jiao, Y Deng, Y Luo, BL Lu - Neurocomputing, 2020 - Elsevier
In recent years, sleepiness during driving has become a main cause for traffic accidents.
However, the fact is that we know very little yet about the electrophysiological marker for …
However, the fact is that we know very little yet about the electrophysiological marker for …
Resting-state EEG power and connectivity are associated with alpha peak frequency slowing in healthy aging
The individual alpha peak frequency (IAPF) of the human electroencephalography (EEG)
typically experiences slowing with increasing age. Despite this hallmark change, studies that …
typically experiences slowing with increasing age. Despite this hallmark change, studies that …
A review of automated techniques for assisting the early detection of Alzheimer's disease with a focus on EEG
E Perez-Valero, MA Lopez-Gordo… - Journal of …, 2021 - content.iospress.com
In this paper, we review state-of-the-art approaches that apply signal processing (SP) and
machine learning (ML) to automate the detection of Alzheimer's disease (AD) and its …
machine learning (ML) to automate the detection of Alzheimer's disease (AD) and its …
Complexity of EEG dynamics for early diagnosis of Alzheimer's disease using permutation entropy neuromarker
Background and objective Electroencephalogram (EEG) is one of the most demanded
screening tools that investigates the effects of Alzheimer's Disease (AD) on human brain …
screening tools that investigates the effects of Alzheimer's Disease (AD) on human brain …
[HTML][HTML] A self-driven approach for multi-class discrimination in Alzheimer's disease based on wearable EEG
E Perez-Valero, MÁ Lopez-Gordo, CM Gutiérrez… - Computer Methods and …, 2022 - Elsevier
Early detection is critical to control Alzheimer's disease (AD) progression and postpone
cognitive decline. Traditional medical procedures such as magnetic resonance imaging are …
cognitive decline. Traditional medical procedures such as magnetic resonance imaging are …
Robust EEG based biomarkers to detect Alzheimer's disease
Biomarkers to detect Alzheimer's disease (AD) would enable patients to gain access to
appropriate services and may facilitate the development of new therapies. Given the large …
appropriate services and may facilitate the development of new therapies. Given the large …
Early diagnosis of mild cognitive impairment and Alzheimer's with event-related potentials and event-related desynchronization in N-back working memory tasks
Abstract Background and Objective: In this study we investigate whether or not event-related
potentials (ERP) and/or event-related (de) synchronization (ERD/ERS) can be used to …
potentials (ERP) and/or event-related (de) synchronization (ERD/ERS) can be used to …
An integrated MCI detection framework based on spectral-temporal analysis
Aiming to differentiate between mild cognitive impairment (MCI) patients and elderly control
subjects, this study proposes an integrated framework based on spectral-temporal analysis …
subjects, this study proposes an integrated framework based on spectral-temporal analysis …