Application and Development of EEG Acquisition and Feedback Technology: A Review

Y Qin, Y Zhang, Y Zhang, S Liu, X Guo - Biosensors, 2023 - mdpi.com
This review focuses on electroencephalogram (EEG) acquisition and feedback technology
and its core elements, including the composition and principles of the acquisition devices, a …

Clinical Analysis of EEG for Cognitive Activation Using MATLAB Applications

RK Kanna, U Mutheeswaran, KA Jabbar… - 2023 3rd …, 2023 - ieeexplore.ieee.org
The pomodoro technique is a helpful study method for managing time. The technique,
developed by Francesco Cirillo in the late 1980s, is an attempt to cram as much learning as …

Reproducible machine learning research in mental workload classification using EEG

G Demirezen, T Taşkaya Temizel… - Frontiers in …, 2024 - frontiersin.org
This study addresses concerns about reproducibility in scientific research, focusing on the
use of electroencephalography (EEG) and machine learning to estimate mental workload …

An EEG Dataset of Neural Signatures in a Competitive Two-Player Game Encouraging Deceptive Behavior

Y Chen, S Fazli, C Wallraven - Scientific data, 2024 - nature.com
Studying deception is vital for understanding decision-making and social dynamics. Recent
EEG research has deepened insights into the brain mechanisms behind deception …

Unobtrusive measurement of cognitive load and physiological signals in uncontrolled environments

C Anders, S Moontaha, S Real, B Arnrich - Scientific Data, 2024 - nature.com
While individuals fail to assess their mental health subjectively in their day-to-day activities,
the recent development of consumer-grade wearable devices has enormous potential to …

[HTML][HTML] NeuroIDBench: An open-source benchmark framework for the standardization of methodology in brainwave-based authentication research

AK Chaurasia, M Fallahi, T Strufe, P Terhörst… - Journal of Information …, 2024 - Elsevier
Biometric systems based on brain activity have been proposed as an alternative to
passwords or to complement current authentication techniques. By leveraging the unique …

Enhancing EEG-based cross-day mental workload classification using periodic component of power spectrum

Y Ke, T Wang, F He, S Liu, D Ming - Journal of Neural …, 2023 - iopscience.iop.org
Objective. The day-to-day variability of electroencephalogram (EEG) poses a significant
challenge to decode human brain activity in EEG-based passive brain-computer interfaces …

Using Semi-supervised Domain Adaptation to Enhance EEG-Based Cross-Task Mental Workload Classification Performance

T Wang, Y Ke, Y Huang, F He, W Zhong… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Mental workload (MWL) assessment is critical for accident prevention and operator safety.
However, achieving cross-task generalization of MWL classification models is a significant …

[HTML][HTML] MST-net: A multi-scale swin transformer network for EEG-based cognitive load assessment

Z Li, R Zhang, Y Zeng, L Tong, R Lu, B Yan - Brain Research Bulletin, 2024 - Elsevier
Cognitive load assessment plays a crucial role in monitoring safe production, resource
allocation, and subjective initiative in human-computer interaction. Due to its high time …

A cross-attention swin transformer network for EEG-based subject-independent cognitive load assessment

Z Li, R Zhang, L Tong, Y Zeng, Y Gao, K Yang… - Cognitive …, 2024 - Springer
EEG signals play a crucial role in assessing cognitive load, which is a key element in
ensuring the secure operation of human–computer interaction systems. However, the …