There has been an increasing trend towards the use of complexity analysis in quantifying
neural activity measured by electroencephalography (EEG) signals. On top of revealing …

Preserving cognition and mental capacity is critical to aging with autonomy. Early detection
of pathological cognitive decline facilitates the greatest impact of restorative or preventative …

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 …

Objective. This study aimed to produce a novel deep learning (DL) model for the
classification of subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI) …

Functional connectivity of the human brain, representing statistical dependence of
information flow between cortical regions, significantly contributes to the study of the intrinsic …

Electroencephalography (EEG) is widely used as a non-invasive technique for the diagnosis
of several brain disorders, including Alzheimer's disease and epilepsy. Until recently …

This study will concentrate on recent research on EEG signals for Alzheimer's diagnosis,
identifying and comparing key steps of EEG‐based Alzheimer's disease (AD) detection …

Elderly people affected by Mild Cognitive Impairment (MCI) usually report a perceived
decline in cognitive functions that deeply impacts their quality of life. This subtle waning …

Alzheimer's disease is the most common cause of dementia, gradually impairing memory,
intellectual, learning, and organizational capacities. An individual's capacity to perform …

Alzheimer's disease (AD) is a neurodegenerative disorder with high prevalence, known for
its highly disabling symptoms. The aim of this study was to characterize the alterations in the …