[HTML][HTML] Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis
Electroencephalography (EEG) is an important tool for studying the human brain activity and
epileptic processes in particular. EEG signals provide important information about …
epileptic processes in particular. EEG signals provide important information about …
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
Mental disorders represent critical public health challenges as they are leading contributors
to the global burden of disease and intensely influence social and financial welfare of …
to the global burden of disease and intensely influence social and financial welfare of …
Automated EEG-based screening of depression using deep convolutional neural network
In recent years, advanced neurocomputing and machine learning techniques have been
used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In …
used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In …
DeprNet: A deep convolution neural network framework for detecting depression using EEG
Depression is a common reason for an increase in suicide cases worldwide. Thus, to
mitigate the effects of depression, accurate diagnosis and treatment are needed. An …
mitigate the effects of depression, accurate diagnosis and treatment are needed. An …
DepHNN: a novel hybrid neural network for electroencephalogram (EEG)-based screening of depression
Depression is a psychological disorder characterized by the continuous occurrence of bad
mood state. It is critical to understand that this disorder is severely affecting people of …
mood state. It is critical to understand that this disorder is severely affecting people of …
Automated depression detection using deep representation and sequence learning with EEG signals
Depression affects large number of people across the world today and it is considered as
the global problem. It is a mood disorder which can be detected using …
the global problem. It is a mood disorder which can be detected using …
A pervasive approach to EEG‐based depression detection
H Cai, J Han, Y Chen, X Sha, Z Wang, B Hu… - …, 2018 - Wiley Online Library
Nowadays, depression is the world's major health concern and economic burden worldwide.
However, due to the limitations of current methods for depression diagnosis, a pervasive …
However, due to the limitations of current methods for depression diagnosis, a pervasive …
Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach
Deep learning techniques have recently made considerable advances in the field of artificial
intelligence. These methodologies can assist psychologists in early diagnosis of mental …
intelligence. These methodologies can assist psychologists in early diagnosis of mental …
A novel depression diagnosis index using nonlinear features in EEG signals
Depression is a mental disorder characterized by persistent occurrences of lower mood
states in the affected person. The electroencephalogram (EEG) signals are highly complex …
states in the affected person. The electroencephalogram (EEG) signals are highly complex …
Decision support system for major depression detection using spectrogram and convolution neural network with EEG signals
Abstract The number of Major Depressive Disorder (MDD) patients is rising rapidly these
days following the incidence of COVID‐19 pandemic. It is challenging to detect MDD …
days following the incidence of COVID‐19 pandemic. It is challenging to detect MDD …