Early diagnosis of Alzheimer's disease: the role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts
PM Rossini, R Di Iorio, F Vecchio, M Anfossi… - Clinical …, 2020 - Elsevier
Alzheimer's disease (AD) is the most common neurodegenerative disease among the
elderly with a progressive decline in cognitive function significantly affecting quality of life …
elderly with a progressive decline in cognitive function significantly affecting quality of life …
Medical big data: neurological diseases diagnosis through medical data analysis
Diagnosis of neurological diseases is a growing concern and one of the most difficult
challenges for modern medicine. According to the World Health Organisation's recent report …
challenges for modern medicine. According to the World Health Organisation's recent report …
EEG microstate sequences in healthy humans at rest reveal scale-free dynamics
D Van de Ville, J Britz… - Proceedings of the …, 2010 - National Acad Sciences
Recent findings identified electroencephalography (EEG) microstates as the
electrophysiological correlates of fMRI resting-state networks. Microstates are defined as …
electrophysiological correlates of fMRI resting-state networks. Microstates are defined as …
Depression recognition based on the reconstruction of phase space of EEG signals and geometrical features
Depression is a mental disorder that continues to make life difficult or impossible for a
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
depressed person and, if left untreated, can lead to dangerous activities such as self-harm …
EEG feature fusion for motor imagery: A new robust framework towards stroke patients rehabilitation
Stroke is the second foremost cause of death worldwide and is one of the most common
causes of disability. Several approaches have been proposed to manage stroke patient …
causes of disability. Several approaches have been proposed to manage stroke patient …
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 …
An automated diagnosis of depression using three-channel bandwidth-duration localized wavelet filter bank with EEG signals
Depression is a mental illness. If not diagnosed and treated quickly, it can affect one's mood
and quality of life. Modern life is stressful and fast paced, owing to which depression has …
and quality of life. Modern life is stressful and fast paced, owing to which depression has …
Automatic detection of Alzheimer's disease from EEG signals using low-complexity orthogonal wavelet filter banks
Background: Alzheimer's disease (AD) is one of the most common neurodegenerative
disorder. As the incidence of AD is rapidly increasing worldwide, detecting it at an early …
disorder. As the incidence of AD is rapidly increasing worldwide, detecting it at an early …
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 …
Alzheimer's diseases diagnosis using fusion of high informative BiLSTM and CNN features of EEG signal
M Imani - Biomedical Signal Processing and Control, 2023 - Elsevier
Electroencephalography (EEG) signals are low cost and available data for diagnosis of
mental disorders such as Alzheimer's diseases (AD). Each EEG signal contains information …
mental disorders such as Alzheimer's diseases (AD). Each EEG signal contains information …