Early Alzheimer's disease diagnosis based on EEG spectral images using deep learning
X Bi, H Wang - Neural Networks, 2019 - Elsevier
Early diagnosis of Alzheimer's disease (AD) is a proceeding hot issue along with a sharp
upward trend in the incidence rate. Recently, early diagnosis of AD employing …
upward trend in the incidence rate. Recently, early diagnosis of AD employing …
Diagnosis of mild Alzheimer's disease by EEG and ERP signals using linear and nonlinear classifiers
A new method for the diagnosis of Alzheimer's disease in the mild stage is presented due to
its association with the characteristics of the EEG brain signal. In the proposed method, three …
its association with the characteristics of the EEG brain signal. In the proposed method, three …
Automated epileptic seizure waveform detection method based on the feature of the mean slope of wavelet coefficient counts using a hidden Markov model and EEG …
Long‐term electroencephalography (EEG) monitoring is time‐consuming, and requires
experts to interpret EEG signals to detect seizures in patients. In this paper, we propose a …
experts to interpret EEG signals to detect seizures in patients. In this paper, we propose a …
A novel EEG-complexity-based feature and its application on the epileptic seizure detection
SL Zhang, B Zhang, YL Su, JL Song - International Journal of Machine …, 2019 - Springer
The neurophysiology system is a complex network of nerves and cells, which carries
messages to and from the brain and spinal cord to various parts of the body. Exploring …
messages to and from the brain and spinal cord to various parts of the body. Exploring …
A systematic mapping of feature extraction and feature selection methods of electroencephalogram signals for neurological diseases diagnostic assistance
WF de Almeida, CA de Moraes Lima… - IEEE Latin America …, 2021 - ieeexplore.ieee.org
Electroencephalogram (EEG) is a non-invasive tool used to monitor the electrical activities of
the brain. EEG signal analysis has several applications in the medical field. It is widely used …
the brain. EEG signal analysis has several applications in the medical field. It is widely used …
[PDF][PDF] Early detection of alzheimer's disease with nonlinear features of eeg signal and mri images by convolutional neural network
Background: The main purpose of this study is to provide a method for early diagnosis of
Alzheimer's disease. This disease reduces memory function by destroying neurons in the …
Alzheimer's disease. This disease reduces memory function by destroying neurons in the …