Diagnosis of Alzheimer's disease from EEG signals: where are we standing?
This paper reviews recent progress in the diagnosis of Alzheimer's disease (AD) from
electroencephalograms (EEG). Three major effects of AD on EEG have been observed …
electroencephalograms (EEG). Three major effects of AD on EEG have been observed …
Complexity analysis of EEG, MEG, and fMRI in mild cognitive impairment and Alzheimer's disease: a review
J Sun, B Wang, Y Niu, Y Tan, C Fan, N Zhang, J Xue… - Entropy, 2020 - mdpi.com
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 …
incidence. In recent years, because brain signals have complex nonlinear dynamics, there …
[HTML][HTML] Adazd-Net: Automated adaptive and explainable Alzheimer's disease detection system using EEG signals
SK Khare, UR Acharya - Knowledge-Based Systems, 2023 - Elsevier
Background: Alzheimer's disease (AZD) is a degenerative neurological condition that
causes dementia and leads the brain to atrophy. Although AZD cannot be cured, early …
causes dementia and leads the brain to atrophy. Although AZD cannot be cured, early …
Classification of focal and non focal EEG using entropies
N Arunkumar, K Ramkumar, V Venkatraman… - Pattern Recognition …, 2017 - Elsevier
Electroencephalogram (EEG) is the recording of the electrical activity of the brain which can
be used to identify different disease conditions. In the case of a partial epilepsy, some …
be used to identify different disease conditions. In the case of a partial epilepsy, some …
Application of entropy measures on intrinsic mode functions for the automated identification of focal electroencephalogram signals
The brain is a complex structure made up of interconnected neurons, and its electrical
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
activities can be evaluated using electroencephalogram (EEG) signals. The characteristics …
EntropyHub: An open-source toolkit for entropic time series analysis
An increasing number of studies across many research fields from biomedical engineering
to finance are employing measures of entropy to quantify the regularity, variability or …
to finance are employing measures of entropy to quantify the regularity, variability or …
Entropy analysis of the EEG background activity in Alzheimer's disease patients
Alzheimer's disease (AD) is the most common neurodegenerative disorder. Although a
definite diagnosis is only possible by necropsy, a differential diagnosis with other types of …
definite diagnosis is only possible by necropsy, a differential diagnosis with other types of …
Diagnosis of Alzheimer's disease with Electroencephalography in a differential framework
N Houmani, F Vialatte, E Gallego-Jutglà, G Dreyfus… - PloS one, 2018 - journals.plos.org
This study addresses the problem of Alzheimer's disease (AD) diagnosis with
Electroencephalography (EEG). The use of EEG as a tool for AD diagnosis has been widely …
Electroencephalography (EEG). The use of EEG as a tool for AD diagnosis has been widely …
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 …
Analysis of complexity in the EEG activity of Parkinson's disease patients by means of approximate entropy
C Pappalettera, F Miraglia, M Cotelli, PM Rossini… - GeroScience, 2022 - Springer
The objective of the present study is to explore the brain resting state differences between
Parkinson's disease (PD) patients and age-and gender-matched healthy controls (elderly) in …
Parkinson's disease (PD) patients and age-and gender-matched healthy controls (elderly) in …