[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 …
A dataset of scalp EEG recordings of Alzheimer's disease, frontotemporal dementia and healthy subjects from routine EEG
Recently, there has been a growing research interest in utilizing the electroencephalogram
(EEG) as a non-invasive diagnostic tool for neurodegenerative diseases. This article …
(EEG) as a non-invasive diagnostic tool for neurodegenerative diseases. This article …
Unveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Text
The conversion of brain activity into text using electroencephalography (EEG) has gained
significant traction in recent years. Many researchers are working to develop new models to …
significant traction in recent years. Many researchers are working to develop new models to …
EEG entropy insights in the context of physiological aging and Alzheimer's and Parkinson's diseases: a comprehensive review
A Cacciotti, C Pappalettera, F Miraglia, PM Rossini… - GeroScience, 2024 - Springer
In recent decades, entropy measures have gained prominence in neuroscience due to the
nonlinear behaviour exhibited by neural systems. This rationale justifies the application of …
nonlinear behaviour exhibited by neural systems. This rationale justifies the application of …
GC‐CNNnet: Diagnosis of Alzheimer's Disease with PET Images Using Genetic and Convolutional Neural Network
There is a wide variety of effects of Alzheimer's disease (AD), a neurodegenerative disease
that can lead to cognitive decline, deterioration of daily life, and behavioral and …
that can lead to cognitive decline, deterioration of daily life, and behavioral and …
Efficient identification of Alzheimer's brain dynamics with Spatial-Temporal Autoencoder: A deep learning approach for diagnosing brain disorders
L Wu, Q Zhao, J Liu, H Yu - Biomedical Signal Processing and Control, 2023 - Elsevier
Alzheimer's disease (AD) is a progressive neurological disorder seriously affecting cognitive
and behavior abilities of the older people. Accurate and early diagnosis of AD is critical for …
and behavior abilities of the older people. Accurate and early diagnosis of AD is critical for …
Identifying biomarkers for tDCS treatment response in Alzheimer's disease patients: a machine learning approach using resting-state EEG classification
SM Andrade, L da Silva-Sauer… - Frontiers in Human …, 2023 - frontiersin.org
Background Transcranial direct current stimulation (tDCS) is a promising treatment for
Alzheimer's Disease (AD). However, identifying objective biomarkers that can predict brain …
Alzheimer's Disease (AD). However, identifying objective biomarkers that can predict brain …
Enhanced Alzheimer's disease and Frontotemporal Dementia EEG Detection: Combining lightGBM Gradient Boosting with Complexity Features
Alzheimer's disease and Frontotemporal dementia are the two most reported dementia
cases. They both are neurodegenerative disorders without cure while existing treatments …
cases. They both are neurodegenerative disorders without cure while existing treatments …
[HTML][HTML] An empirical wavelet transform-based approach for motion artifact removal in electroencephalogram signals
AB Nayak, A Shah, S Maheshwari, V Anand… - Decision Analytics …, 2024 - Elsevier
Motion artifacts reduce the quality of information in the electroencephalogram (EEG) signals.
In this study, we have developed an effective approach to mitigate the motion artifacts in …
In this study, we have developed an effective approach to mitigate the motion artifacts in …
Neural markers of reduced arousal and consciousness in mild cognitive impairment
Abstract Objectives People with Alzheimer's Disease (AD) experience changes in their level
and content of consciousness, but there is little research on biomarkers of consciousness in …
and content of consciousness, but there is little research on biomarkers of consciousness in …