Recognition of human emotions using EEG signals: A review

MM Rahman, AK Sarkar, MA Hossain… - Computers in biology …, 2021 - Elsevier
Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …

A review on evaluating mental stress by deep learning using EEG signals

Y Badr, U Tariq, F Al-Shargie, F Babiloni… - Neural Computing and …, 2024 - Springer
Mental stress is a common problem that affects individuals all over the world. Stress reduces
human functionality during routine work and may lead to severe health defects. Early …

Prediction of depression severity scores based on functional connectivity and complexity of the EEG signal

Y Mohammadi, MH Moradi - Clinical EEG and Neuroscience, 2021 - journals.sagepub.com
Background Depression is one of the most common mental disorders and the leading cause
of functional disabilities. This study aims to specify whether functional connectivity and …

[PDF][PDF] Metabolism of methylenedioxymethamphetamine: formation of dihydroxymethamphetamine and a quinone identified as its glutathione adduct.

M Hiramatsu, Y Kumagai, SE Unger, AK Cho - Journal of Pharmacology …, 1990 - Citeseer
The in vitro conversion of (+)-3, 4-methylenedioxymethamphe-tamine and (-)-3, 4-
methylenedioxymethamphetamine to the corresponding catecholamine, 3, 4 …

Paving the way for future EEG studies in construction: dependent component analysis for automatic ocular artifact removal from brainwave signals

Y Liu, M Habibnezhad, S Shayesteh… - Journal of …, 2021 - ascelibrary.org
Construction workers' poor mental states can lead to numerous safety and productivity
issues. One major trend in construction research is quantitatively evaluating workers' …

Spatial-temporal dynamic hypergraph information bottleneck for brain network classification

C Dong, D Sun - International journal of neural systems, 2024 - pubmed.ncbi.nlm.nih.gov
Recently, Graph Neural Networks (GNNs) have gained widespread application in automatic
brain network classification tasks, owing to their ability to directly capture crucial information …

Is there frequency-specificity in the motor control of walking? The putative differential role of alpha and beta oscillations

CC Charalambous, A Hadjipapas - Frontiers in Systems …, 2022 - frontiersin.org
Alpha and beta oscillations have been assessed thoroughly during walking due to their
potential role as proxies of the corticoreticulospinal tract (CReST) and corticospinal tract …

Brain network classification based on dynamic graph attention information bottleneck

C Dong, D Sun - Computer Methods and Programs in Biomedicine, 2024 - Elsevier
Abstract Background and Objectives Graph neural networks (GNN) have demonstrated
remarkable encoding capabilities in the context of brain network classification tasks. They …

Development of LSTM&CNN based hybrid deep learning model to classify motor imagery tasks

C Uyulan - bioRxiv, 2020 - biorxiv.org
Recent studies underline the contribution of brain-computer interface (BCI) applications to
the enhancement process of the life quality of physically impaired subjects. In this context, to …

Independent low-rank matrix analysis-based automatic artifact reduction technique applied to three BCI paradigms

S Kanoga, T Hoshino, H Asoh - Frontiers in Human Neuroscience, 2020 - frontiersin.org
Electroencephalogram (EEG)-based brain-computer interfaces (BCIs) can potentially enable
people to non-invasively and directly communicate with others using brain activities. Artifacts …