A systematic review and methodological analysis of EEG-based biomarkers of Alzheimer's disease
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders in the
world. Although there is no known cure for it at the present, preventive drug trials and …
world. Although there is no known cure for it at the present, preventive drug trials and …
[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 …
Review of EEG-based biometrics in 5G-IoT: Current trends and future prospects
The increasing integration of the Internet of Things (IoT) into daily life has led to significant
changes in our social interactions. The advent of innovative IoT solutions, combined with the …
changes in our social interactions. The advent of innovative IoT solutions, combined with the …
Efficient deep neural networks for classification of Alzheimer's disease and mild cognitive impairment from scalp EEG recordings
The early diagnosis of subjects with mild cognitive impairment (MCI) is an effective
appliance of prognosis of Alzheimer's disease (AD). Electroencephalogram (EEG) has many …
appliance of prognosis of Alzheimer's disease (AD). Electroencephalogram (EEG) has many …
Primate brain pattern-based automated Alzheimer's disease detection model using EEG signals
Electroencephalography (EEG) may detect early changes in Alzheimer's disease (AD), a
debilitating progressive neurodegenerative disease. We have developed an automated AD …
debilitating progressive neurodegenerative disease. We have developed an automated AD …
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 …
[HTML][HTML] A novel optimal wavelet filter banks for automated diagnosis of Alzheimer's disease and mild cognitive impairment using Electroencephalogram signals
Electroencephalogram (EEG) of Alzheimer's disease (AD) patients show a slowing effect
and less synchronization. EEG signal's transient and abrupt nature is captured from various …
and less synchronization. EEG signal's transient and abrupt nature is captured from various …
A greedy optimized intelligent framework for early detection of Alzheimer's disease using EEG signal
R Swarnalatha - Computational Intelligence and Neuroscience, 2023 - Wiley Online Library
Recent researchers have been drawn to the analysis of electroencephalogram (EEG)
signals in order to confirm the disease and severity range by viewing the EEG signal which …
signals in order to confirm the disease and severity range by viewing the EEG signal which …
Alzheimer's disease detection using empirical mode decomposition and Hjorth parameters of EEG signal
Alzheimer's disease (AD) is a progressive neuro-degenerative disorder observed in the
elderly. AD diagnosis is performed through interviews or questionnaires by an experienced …
elderly. AD diagnosis is performed through interviews or questionnaires by an experienced …
Alzheimer's disease analysis algorithm based on no-threshold recurrence plot convolution network
X Li, T Zhou, S Qiu - Frontiers in Aging Neuroscience, 2022 - frontiersin.org
Alzheimer's disease is a neurological disorder characterized by progressive cognitive
dysfunction and behavioral impairment that occurs in old. Early diagnosis and treatment of …
dysfunction and behavioral impairment that occurs in old. Early diagnosis and treatment of …