A review on evaluating mental stress by deep learning using EEG signals
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 …
human functionality during routine work and may lead to severe health defects. Early …
Spatial–temporal co-attention learning for diagnosis of mental disorders from resting-state fMRI data
Neuroimaging techniques have been widely adopted to detect the neurological brain
structures and functions of the nervous system. As an effective noninvasive neuroimaging …
structures and functions of the nervous system. As an effective noninvasive neuroimaging …
A spiking neural network with adaptive graph convolution and lstm for eeg-based brain-computer interfaces
Electroencephalography (EEG) signals classification is essential for the brain-computer
interface (BCI). Recently, energy-efficient spiking neural networks (SNNs) have shown great …
interface (BCI). Recently, energy-efficient spiking neural networks (SNNs) have shown great …
Dynamic alignment and fusion of multimodal physiological patterns for stress recognition
X Zhang, X Wei, Z Zhou, Q Zhao… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Stress has been identified as one of major causes of health issues. To detect the stress
levels with higher accuracy, fusion of multimodal physiological signals is a promising …
levels with higher accuracy, fusion of multimodal physiological signals is a promising …
Mental workload assessment using deep learning models from EEG signals: a systematic review
K Kingphai, Y Moshfeghi - IEEE Transactions on Cognitive and …, 2024 - ieeexplore.ieee.org
Mental workload (MWL) assessment is crucial in information systems (IS), impacting task
performance, user experience, and system effectiveness. Deep learning offers promising …
performance, user experience, and system effectiveness. Deep learning offers promising …
MuLDOM: Forecasting Multivariate Anomalies on Edge Devices in IIoT Using Multibranch LSTM and Differential Overfitting Mitigation Model
P Li, M Wu, Y Zhang, J Xia… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
In the Industrial Internet of Things (IIoT) environment, there is a multitude of heterogeneous
industrial edge devices (IEDs) from various sources. Real-time monitoring and precise …
industrial edge devices (IEDs) from various sources. Real-time monitoring and precise …
Classification of post-covid-19 emotions with residual-based separable convolution networks and eeg signals
The COVID-19 epidemic has created highly unprocessed emotions that trigger stress,
anxiety, or panic attacks. These attacks exhibit physical symptoms that may easily lead to …
anxiety, or panic attacks. These attacks exhibit physical symptoms that may easily lead to …
ARFN: An Attention-Based Recurrent Fuzzy Network for EEG Mental Workload Assessment
Assessing mental workload using electroencephalogram (EEG) signals is a significant
research avenue within the brain–computer interface (BCI) domain. However, due to the low …
research avenue within the brain–computer interface (BCI) domain. However, due to the low …
Exploring EEG characteristics of multi-level mental stress based on human–machine system
Q Yao, H Gu, S Wang, G Liang… - Journal of Neural …, 2023 - iopscience.iop.org
Objective. The understanding of cognitive states is important for the development of human–
machine systems (HMSs), and one of the fundamental but challenging issues is the …
machine systems (HMSs), and one of the fundamental but challenging issues is the …
Movement Artifact Suppression in Wearable Low-Density and Dry EEG Recordings Using Active Electrodes and Artifact Subspace Reconstruction
SY Yang, YP Lin - IEEE Transactions on Neural Systems and …, 2023 - ieeexplore.ieee.org
Wearable low-density dry electroencephalogram (EEG) headsets facilitate multidisciplinary
applications of brain-activity decoding and brain-triggered interaction for healthy people in …
applications of brain-activity decoding and brain-triggered interaction for healthy people in …