[HTML][HTML] Frontal lobe real-time EEG analysis using machine learning techniques for mental stress detection
Stress has become a dangerous health problem in our life, especially in student education
journey. Accordingly, previous methods have been conducted to detect mental stress based …
journey. Accordingly, previous methods have been conducted to detect mental stress based …
Multimodal fusion of EEG-fNIRS: a mutual information-based hybrid classification framework
RJ Deligani, SB Borgheai, J McLinden… - Biomedical optics …, 2021 - opg.optica.org
Multimodal data fusion is one of the current primary neuroimaging research directions to
overcome the fundamental limitations of individual modalities by exploiting complementary …
overcome the fundamental limitations of individual modalities by exploiting complementary …
Fusing near-infrared spectroscopy with wearable hemodynamic measurements improves classification of mental stress
Human-computer interaction technology, and the automatic classification of a person's
mental state, are of interest to multiple industries. In this paper, the fusion of sensing …
mental state, are of interest to multiple industries. In this paper, the fusion of sensing …
A deep learning-based approach for distinguishing different stress levels of human brain using EEG and pulse rate
P Mukherjee, A Halder Roy - Computer Methods in Biomechanics …, 2023 - Taylor & Francis
In today's world, people suffer from many fatal maladies, and stress is one of them.
Excessive stress can have deleterious effects on the health, brain, mind, and nervous …
Excessive stress can have deleterious effects on the health, brain, mind, and nervous …
[HTML][HTML] Hybrid deep learning approach for stress detection using decomposed eeg signals
Stress has an impact, not only on a person's physical health, but also on the ability to
perform at the workplace in daily life. The well-established relation between psychological …
perform at the workplace in daily life. The well-established relation between psychological …
EEG-based detection of cognitive load using VMD and LightGBM classifier
Cognitive load, which alters neuronal activity, is essential to understanding how the brain
reacts to stress. This work aims to classify electroencephalogram (EEG) signals to detect …
reacts to stress. This work aims to classify electroencephalogram (EEG) signals to detect …
[HTML][HTML] Measuring mental workload with EEG+ fNIRS
We studied the capability of a Hybrid functional neuroimaging technique to quantify human
mental workload (MWL). We have used electroencephalography (EEG) and functional near …
mental workload (MWL). We have used electroencephalography (EEG) and functional near …
Machine learning framework for the detection of mental stress at multiple levels
Mental stress has become a social issue and could become a cause of functional disability
during routine work. In addition, chronic stress could implicate several psychophysiological …
during routine work. In addition, chronic stress could implicate several psychophysiological …
[HTML][HTML] EEG mental stress assessment using hybrid multi-domain feature sets of functional connectivity network and time-frequency features
Exposure to mental stress for long period leads to serious accidents and health problems.
To avoid negative consequences on health and safety, it is very important to detect mental …
To avoid negative consequences on health and safety, it is very important to detect mental …
[HTML][HTML] fNIRS evaluation of frontal and temporal cortex activation by verbal fluency task and high-level cognition task for detecting anxiety and depression
X Lang, D Wen, Q Li, Q Yin, M Wang, Y Xu - Frontiers in Psychiatry, 2021 - frontiersin.org
Anxiety and depression are widespread psychosis which are believed to affect cerebral
metabolism, especially in frontal and temporal cortex. The comorbidity patients of anxiety …
metabolism, especially in frontal and temporal cortex. The comorbidity patients of anxiety …