Current trends and opportunities in the methodology of electrodermal activity measurement
Electrodermal activity (EDA) has been measured in the laboratory since the late 1800s.
Although the influence of sudomotor nerve activity and the sympathetic nervous system on …
Although the influence of sudomotor nerve activity and the sympathetic nervous system on …
An insight into diagnosis of depression using machine learning techniques: a systematic review
Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …
from which millions of individuals are affected today. The symptoms of depression are …
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 …
Exploration of physiological sensors, features, and machine learning models for pain intensity estimation
In current clinical settings, typically pain is measured by a patient's self-reported information.
This subjective pain assessment results in suboptimal treatment plans, over-prescription of …
This subjective pain assessment results in suboptimal treatment plans, over-prescription of …
[HTML][HTML] Automatic depression detection using smartphone-based text-dependent speech signals: deep convolutional neural network approach
Background Automatic diagnosis of depression based on speech can complement mental
health treatment methods in the future. Previous studies have reported that acoustic …
health treatment methods in the future. Previous studies have reported that acoustic …
[HTML][HTML] Detection of major depressive disorder from linear and nonlinear heart rate variability features during mental task protocol
S Byun, AY Kim, EH Jang, S Kim, KW Choi… - Computers in biology …, 2019 - Elsevier
Background Major depressive disorder (MDD) is one of the leading causes of disability;
however, current MDD diagnosis methods lack an objective assessment of depressive …
however, current MDD diagnosis methods lack an objective assessment of depressive …
Automated major depressive disorder detection using melamine pattern with EEG signals
Major depressive disorder (MDD) is one of the most common modern ailments affected huge
population throughout the world. The electroencephalogram (EEG) signal is widely used to …
population throughout the world. The electroencephalogram (EEG) signal is widely used to …
Artificial intelligence assisted tools for the detection of anxiety and depression leading to suicidal ideation in adolescents: a review
Epidemiological studies report high levels of anxiety and depression amongst adolescents.
These psychiatric conditions and complex interplays of biological, social and environmental …
These psychiatric conditions and complex interplays of biological, social and environmental …
Shared and distinct brain fMRI response during performance of working memory tasks in adult patients with schizophrenia and major depressive disorder
X Wang, B Cheng, N Roberts, S Wang… - Human brain …, 2021 - Wiley Online Library
Working memory (WM) impairments are common features of psychiatric disorders. A
systematic meta‐analysis was performed to determine common and disorder‐specific brain …
systematic meta‐analysis was performed to determine common and disorder‐specific brain …
[HTML][HTML] Digital phenotyping for differential diagnosis of major depressive episode: narrative review
E Ettore, P Müller, J Hinze, M Riemenschneider… - JMIR mental …, 2023 - mental.jmir.org
Background Major depressive episode (MDE) is a common clinical syndrome. It can be
found in different pathologies such as major depressive disorder (MDD), bipolar disorder …
found in different pathologies such as major depressive disorder (MDD), bipolar disorder …