Diversity and suitability of the state-of-the-art wearable and wireless EEG systems review

C He, YY Chen, CR Phang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Wireless electroencephalography (EEG) systems have been attracting increasing attention
in recent times. Both the number of articles discussing wireless EEG and their proportion …

Cognitive-based crack detection for road maintenance: an integrated system in cyber-physical-social systems

L Fan, D Cao, C Zeng, B Li, Y Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Effective road maintenance can not only achieve a balance between limited resources and
long-term high-efficiency performance of road but also reduce the loss of life and property …

Human brain dynamics in active spatial navigation

TTN Do, CT Lin, K Gramann - Scientific Reports, 2021 - nature.com
Spatial navigation is a complex cognitive process based on multiple senses that are
integrated and processed by a wide network of brain areas. Previous studies have revealed …

P300 brain–computer interface-based drone control in virtual and augmented reality

S Kim, S Lee, H Kang, S Kim, M Ahn - Sensors, 2021 - mdpi.com
Since the emergence of head-mounted displays (HMDs), researchers have attempted to
introduce virtual and augmented reality (VR, AR) in brain–computer interface (BCI) studies …

The roles and modes of human interactions with automated machine learning systems

TT Khuat, DJ Kedziora, B Gabrys - arXiv preprint arXiv:2205.04139, 2022 - arxiv.org
As automated machine learning (AutoML) systems continue to progress in both
sophistication and performance, it becomes important to understand thehow'andwhy'of …

Automatic topology optimization of echo state network based on particle swarm optimization

Y Xue, Q Zhang, A Slowik - Engineering Applications of Artificial …, 2023 - Elsevier
The task of time series forecasting is to predict the future trend of data based on the collected
historical data, providing theoretical and data support for human judgment and decision …

Towards a more theory-driven BCI using source reconstructed dynamics of EEG time-series

R Janapati, V Dalal, R Sengupta, U Desai… - Nano Life, 2022 - World Scientific
Currently, the operational electroencephalography (EEG)-based brain–computer interfaces
(BCIs) suffer from problems of BCI latency/lag issues, which restricts the use of interfaces …

Robust predictive control for EEG-based brain–robot teleoperation

H Li, L Bi, X Li, H Gan - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Brain-teleoperation robot control ensures that human beings interact with telepresence
mobile systems through the brain neural signals. In this study, a hierarchical robust …

The Roles and Modes of Human Interactions with Automated Machine Learning Systems: A Critical Review and Perspectives

TT Khuat, DJ Kedziora, B Gabrys - Foundations and Trends® …, 2023 - nowpublishers.com
As automated machine learning (AutoML) systems continue to progress in both
sophistication and performance, it becomes important to understand the 'how'and 'why'of …

MARS: Multiagent reinforcement learning for spatial–spectral and temporal feature selection in EEG-based BCI

DH Shin, YH Son, JM Kim, HJ Ahn… - … on Systems, Man …, 2024 - ieeexplore.ieee.org
In recent years, deep learning methods have shown promising capabilities for extracting
informative and discriminative features from electroencephalography (EEG) data. However …