[HTML][HTML] Deep learning in physiological signal data: A survey

B Rim, NJ Sung, S Min, M Hong - Sensors, 2020‏ - mdpi.com
Deep Learning (DL), a successful promising approach for discriminative and generative
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

A Sujatha Ravindran, J Contreras-Vidal - Scientific Reports, 2023‏ - nature.com
Recent advancements in machine learning and deep learning (DL) based neural decoders
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

A Mostafavi, JG Cruz-Garza, S Kalantari - Journal of Building Engineering, 2023‏ - Elsevier
Investigating human responses to light can reveal important information with the potential to
improve environmental design, circadian health, cognitive performance, and overall …

Identifying uncertainty states during wayfinding in indoor environments: An EEG classification study

B Zhu, JG Cruz-Garza, Q Yang, M Shoaran… - Advanced Engineering …, 2022‏ - Elsevier
The researchers used a machine-learning classification approach to better understand
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

MA Ramírez-Moreno, P Carrillo-Tijerina… - International journal of …, 2021‏ - mdpi.com
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 …

[HTML][HTML] Reliability map of individual differences reflected in inter-subject correlation in naturalistic imaging

J Gao, G Chen, J Wu, Y Wang, Y Hu, T Xu, XN Zuo… - NeuroImage, 2020‏ - Elsevier
Understanding individual differences in brain function is an essential aim of neuroscience.
Naturalistic imaging links neural activity to real-life contexts and reflects individual …

Brain-to-brain communication during musical improvisation: A performance case study

MA Ramírez-Moreno, JG Cruz-Garza… - …, 2023‏ - pmc.ncbi.nlm.nih.gov
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) …

Deep learning methods for EEG neural classification

S Nakagome, A Craik, A Sujatha Ravindran… - Handbook of …, 2022‏ - Springer
Classification of patterns of brain activity in neuroengineering research is an important tool
for understanding the brain, develo** neurodiagnostics, and designing closed-loop neural …

Bimodal transformer with regional EEG data for accurate gameplay regularity classification

J Lee, JH Han - Brain Sciences, 2024‏ - mdpi.com
As games have been applied across various fields, including education and healthcare,
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

JG Cruz-Garza, M Darfler, JD Rounds, E Gao… - arxiv preprint arxiv …, 2021‏ - arxiv.org
This study investigated the neural dynamics associated with short-term exposure to different
virtual classroom designs with different window placement and room dimension. Participants …