Resting-state EEG signal for major depressive disorder detection: A systematic validation on a large and diverse dataset
Major depressive disorder (MDD) is a global healthcare issue and one of the leading causes
of disability. Machine learning combined with non-invasive electroencephalography (EEG) …
of disability. Machine learning combined with non-invasive electroencephalography (EEG) …
A study of resting-state EEG biomarkers for depression recognition
S Sun, J Li, H Chen, T Gong, X Li, B Hu - arXiv preprint arXiv:2002.11039, 2020 - arxiv.org
Background: Depression has become a major health burden worldwide, and effective
detection depression is a great public-health challenge. This Electroencephalography (EEG) …
detection depression is a great public-health challenge. This Electroencephalography (EEG) …
Comparing resting state and task-based EEG using machine learning to predict vulnerability to depression in a non-clinical population
Abstract Major Depressive Disorder (MDD) affects a large portion of the population and
levies a huge societal burden. It has serious consequences like decreased productivity and …
levies a huge societal burden. It has serious consequences like decreased productivity and …
Major depression detection from EEG signals using kernel eigen-filter-bank common spatial patterns
Major depressive disorder (MDD) has become a leading contributor to the global burden of
disease; however, there are currently no reliable biological markers or physiological …
disease; however, there are currently no reliable biological markers or physiological …
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 …
Development of wavelet coherence EEG as a biomarker for diagnosis of major depressive disorder
DM Khan, K Masroor, MFM Jailani… - IEEE Sensors …, 2022 - ieeexplore.ieee.org
Major depressive disorder (MDD) contributes the most to human's functional frailty
worldwide. Therefore, its timely diagnosis and treatment is of utmost importance …
worldwide. Therefore, its timely diagnosis and treatment is of utmost importance …
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 …
Depression biomarkers using non-invasive EEG: A review
FS de Aguiar Neto, JLG Rosa - Neuroscience & Biobehavioral Reviews, 2019 - Elsevier
Depression is a serious neurological disorder characterized by strong loss of interest,
possibly leading to suicide. According to the World Health Organization, more than 300 …
possibly leading to suicide. According to the World Health Organization, more than 300 …
Automated diagnosis of major depressive disorder using brain effective connectivity and 3D convolutional neural network
Major depressive disorder (MDD), which is also known as unipolar depression, is one of the
leading sources of functional frailty. MDD is mostly a chronic disorder that requires a long …
leading sources of functional frailty. MDD is mostly a chronic disorder that requires a long …
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 …