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[HTML][HTML] Deep learning in physiological signal data: A survey
Deep Learning (DL), a successful promising approach for discriminative and generative
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
tasks, has recently proved its high potential in 2D medical imaging analysis; however …
An empirical comparison of deep learning explainability approaches for EEG using simulated ground truth
Recent advancements in machine learning and deep learning (DL) based neural decoders
have significantly improved decoding capabilities using scalp electroencephalography …
have significantly improved decoding capabilities using scalp electroencephalography …
Enhancing lighting design through the investigation of illuminance and correlated color Temperature's effects on brain activity: An EEG-VR approach
Investigating human responses to light can reveal important information with the potential to
improve environmental design, circadian health, cognitive performance, and overall …
improve environmental design, circadian health, cognitive performance, and overall …
Identifying uncertainty states during wayfinding in indoor environments: An EEG classification study
The researchers used a machine-learning classification approach to better understand
neurological features associated with periods of wayfinding uncertainty. The participants (n …
neurological features associated with periods of wayfinding uncertainty. The participants (n …
[HTML][HTML] Evaluation of a fast test based on biometric signals to assess mental fatigue at the workplace—A pilot study
Non-pathological mental fatigue is a recurring, but undesirable condition among people in
the fields of office work, industry, and education. This type of mental fatigue can often lead to …
the fields of office work, industry, and education. This type of mental fatigue can often lead to …
[HTML][HTML] Reliability map of individual differences reflected in inter-subject correlation in naturalistic imaging
Understanding individual differences in brain function is an essential aim of neuroscience.
Naturalistic imaging links neural activity to real-life contexts and reflects individual …
Naturalistic imaging links neural activity to real-life contexts and reflects individual …
Brain-to-brain communication during musical improvisation: A performance case study
Understanding and predicting others' actions in ecological settings is an important research
goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) …
goal in social neuroscience. Here, we deployed a mobile brain-body imaging (MoBI) …
Deep learning methods for EEG neural classification
Classification of patterns of brain activity in neuroengineering research is an important tool
for understanding the brain, develo** neurodiagnostics, and designing closed-loop neural …
for understanding the brain, develo** neurodiagnostics, and designing closed-loop neural …
Bimodal transformer with regional EEG data for accurate gameplay regularity classification
As games have been applied across various fields, including education and healthcare,
numerous new games tailored to each field have emerged. Therefore, understanding user …
numerous new games tailored to each field have emerged. Therefore, understanding user …
EEG-based investigation of the impact of classroom design on cognitive performance of students
This study investigated the neural dynamics associated with short-term exposure to different
virtual classroom designs with different window placement and room dimension. Participants …
virtual classroom designs with different window placement and room dimension. Participants …