A comparative analysis of signal processing and classification methods for different applications based on EEG signals
A Khosla, P Khandnor, T Chand - Biocybernetics and Biomedical …, 2020 - Elsevier
Electroencephalogram (EEG) measures the neuronal activities in the form of electric
currents that are generated due to the synchronized activity by a group of specialized …
currents that are generated due to the synchronized activity by a group of specialized …
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 …
Early detection of Alzheimer's disease from EEG signals using Hjorth parameters
Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the
brain that ultimately results in the death of neurons and dementia. The prevalence of the …
brain that ultimately results in the death of neurons and dementia. The prevalence of the …
Particle swarm optimization fractional slope entropy: A new time series complexity indicator for bearing fault diagnosis
Y Li, L Mu, P Gao - Fractal and Fractional, 2022 - mdpi.com
Slope entropy (SlEn) is a time series complexity indicator proposed in recent years, which
has shown excellent performance in the fields of medical and hydroacoustics. In order to …
has shown excellent performance in the fields of medical and hydroacoustics. In order to …
Spatial–temporal graph convolutional network for Alzheimer classification based on brain functional connectivity imaging of electroencephalogram
Functional connectivity of the human brain, representing statistical dependence of
information flow between cortical regions, significantly contributes to the study of the intrinsic …
information flow between cortical regions, significantly contributes to the study of the intrinsic …
Machine learning algorithms and statistical approaches for Alzheimer's disease analysis based on resting-state EEG recordings: A systematic review
Alzheimer's Disease (AD) is a neurodegenerative disorder and the most common type of
dementia with a great prevalence in western countries. The diagnosis of AD and its …
dementia with a great prevalence in western countries. The diagnosis of AD and its …
Detection of alzheimer's dementia by using signal decomposition and machine learning methods
Dementia is one of the most common neurological disorders causing defection of cognitive
functions, and seriously affects the quality of life. In this study, various methods have been …
functions, and seriously affects the quality of life. In this study, various methods have been …
A new denoising method based on decomposition mixing of hydro-acoustic signal
G Li, H Yan, H Yang - Ocean Engineering, 2024 - Elsevier
Hydro-acoustic signal (HAS) contains abundant information. HAS denoising is of great
significance for accurate identification of underwater targets, research of military detection …
significance for accurate identification of underwater targets, research of military detection …
EEG window length evaluation for the detection of Alzheimer's disease over different brain regions
Alzheimer's Disease (AD) is a neurogenerative disorder and the most common type of
dementia with a rapidly increasing world prevalence. In this paper, the ability of several …
dementia with a rapidly increasing world prevalence. In this paper, the ability of several …
A new approach for automatic detection of focal EEG signals using wavelet packet decomposition and quad binary pattern method
NJ Sairamya, MSP Subathra… - … Signal Processing and …, 2021 - Elsevier
A comprehensive feature representation for electroencephalogram (EEG) signal to achieve
effective epileptic focus localization using a one-dimensional quad binary pattern (QBP) is …
effective epileptic focus localization using a one-dimensional quad binary pattern (QBP) is …