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 …
Role of EEG as biomarker in the early detection and classification of dementia
The early detection and classification of dementia are important clinical support tasks for
medical practitioners in customizing patient treatment programs to better manage the …
medical practitioners in customizing patient treatment programs to better manage the …
Performance evaluation of DWT based sigmoid entropy in time and frequency domains for automated detection of epileptic seizures using SVM classifier
The electroencephalogram (EEG) signal contains useful information on physiological states
of the brain and has proven to be a potential biomarker to realize the complex dynamic …
of the brain and has proven to be a potential biomarker to realize the complex dynamic …
Effects of rTMS on the brain: is there value in variability?
The ability of repetitive transcranial magnetic stimulation (rTMS) to non-invasively induce
neuroplasticity in the human cortex has opened exciting possibilities for its application in …
neuroplasticity in the human cortex has opened exciting possibilities for its application in …
Complexity measures for quantifying changes in electroencephalogram in Alzheimer's disease
Alzheimer's disease (AD) is a progressive disorder that affects cognitive brain functions and
starts many years before its clinical manifestations. A biomarker that provides a quantitative …
starts many years before its clinical manifestations. A biomarker that provides a quantitative …
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 …
Automatic diagnosis of mild cognitive impairment using electroencephalogram spectral features
M Kashefpoor, H Rabbani… - Journal of Medical Signals …, 2016 - journals.lww.com
Alzheimer's disease (AD) is one of the most expensive and fatal diseases in the elderly
population. Up to now, no cure have been found for AD, so early stage diagnosis is the only …
population. Up to now, no cure have been found for AD, so early stage diagnosis is the only …
LSD-induced increase of Ising temperature and algorithmic complexity of brain dynamics
G Ruffini, G Damiani, D Lozano-Soldevilla… - PLoS computational …, 2023 - journals.plos.org
A topic of growing interest in computational neuroscience is the discovery of fundamental
principles underlying global dynamics and the self-organization of the brain. In particular …
principles underlying global dynamics and the self-organization of the brain. In particular …
Supervised dictionary learning of EEG signals for mild cognitive impairment diagnosis
M Kashefpoor, H Rabbani, M Barekatain - Biomedical Signal Processing …, 2019 - Elsevier
Abstract Mild Cognitive Impairment (MCI) is an intermediate stage of memory decline
between normal aging and Alzheimer's disease or other types of dementia. MCI diagnosis is …
between normal aging and Alzheimer's disease or other types of dementia. MCI diagnosis is …
Tsallis entropy as a biomarker for detection of Alzheimer's disease
Alzheimer's disease (AD) and other forms of dementia are one of the major public health
and social challenges of our time because of the large number of people affected. Early …
and social challenges of our time because of the large number of people affected. Early …