A novel EEG-based major depressive disorder detection framework with two-stage feature selection
Background Major depressive disorder (MDD) is a common mental illness, characterized by
persistent depression, sadness, despair, etc., troubling people's daily life and work seriously …
persistent depression, sadness, despair, etc., troubling people's daily life and work seriously …
Spatial–temporal eeg fusion based on neural network for major depressive disorder detection
B Zhang, D Wei, G Yan, X Li, Y Su, H Cai - … Sciences: Computational Life …, 2023 - Springer
In view of the major depressive disorder characteristics such as high mortality as well as
high recurrence, it is important to explore an objective and effective detection method for …
high recurrence, it is important to explore an objective and effective detection method for …
MDD-TSVM: A novel semisupervised-based method for major depressive disorder detection using electroencephalogram signals
Major depressive disorder (MDD) is a common mental illness characterized by persistent
feeling of depressed mood and loss of interest. It would cause, in a severe case, suicide …
feeling of depressed mood and loss of interest. It would cause, in a severe case, suicide …
EEG-based mild depressive detection using differential evolution
Depression has become a serious disease that affects people's mental health. How to detect
it promptly and accurately is a difficult task. Electroencephalogram can reflect the …
it promptly and accurately is a difficult task. Electroencephalogram can reflect the …
LSDD-EEGNet: An efficient end-to-end framework for EEG-based depression detection
XW Song, DD Yan, LL Zhao, LC Yang - Biomedical Signal Processing and …, 2022 - Elsevier
Depression is a mood disorder that causes negative effects on people's life and has become
a leading health burden worldwide. But the effective and low-cost detection for depression is …
a leading health burden worldwide. But the effective and low-cost detection for depression is …
An end-to-end deep learning model for EEG-based major depressive disorder classification
M Xia, Y Zhang, Y Wu, X Wang - IEEE Access, 2023 - ieeexplore.ieee.org
Major depressive disorder (MDD) is a prevalent mental illness associated with abnormalities
in structural and functional brain connectivity, which has become a global public health …
in structural and functional brain connectivity, which has become a global public health …
Automated detection of major depressive disorder with EEG signals: a time series classification using deep learning
Major depressive disorder (MDD) has been considered a severe and common ailment with
effects on functional frailty, while its clear manifestations are shrouded in mystery. Hence …
effects on functional frailty, while its clear manifestations are shrouded in mystery. Hence …
EEG-based mild depressive detection using feature selection methods and classifiers
X Li, B Hu, S Sun, H Cai - Computer methods and programs in biomedicine, 2016 - Elsevier
Background and objective Depression has become a major health burden worldwide, and
effectively detection of such disorder is a great challenge which requires latest technological …
effectively detection of such disorder is a great challenge which requires latest technological …
A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis
RA Movahed, GP Jahromi, S Shahyad… - Journal of Neuroscience …, 2021 - Elsevier
Background Major depressive disorder (MDD) is a prevalent mental illness that is diagnosed
through questionnaire-based approaches; however, these methods may not lead to an …
through questionnaire-based approaches; however, these methods may not lead to an …
A multiview sparse dynamic graph convolution-based region-attention feature fusion network for major depressive disorder detection
Detecting and diagnosing major depressive disorder (MDD) is greatly crucial for appropriate
treatment and support. In recent years, there have been efforts to develop automated …
treatment and support. In recent years, there have been efforts to develop automated …