[HTML][HTML] Signal acquisition of brain-computer interfaces: a medical-engineering crossover perspective review

Y Sun, X Chen, B Liu, L Liang, Y Wang, S Gao… - Fundamental …, 2024 - Elsevier
Brain-computer interface (BCI) technology represents a burgeoning interdisciplinary domain
that facilitates direct communication between individuals and external devices. The efficacy …

Industrial metaverse: Connotation, features, technologies, applications and challenges

Z Zheng, T Li, B Li, X Chai, W Song, N Chen… - Asian simulation …, 2022 - Springer
Metaverse expands the cyberspace with more emphasis on human-in-loop interaction,
value definition of digital assets and real-virtual reflection, which facilitates the organic fusion …

Wearable EEG electronics for a Brain–AI Closed-Loop System to enhance autonomous machine decision-making

JH Shin, J Kwon, JU Kim, H Ryu, J Ok… - npj Flexible …, 2022 - nature.com
Human nonverbal communication tools are very ambiguous and difficult to transfer to
machines or artificial intelligence (AI). If the AI understands the mental state behind a user's …

Cross-dataset transfer learning for motor imagery signal classification via multi-task learning and pre-training

Y **e, K Wang, J Meng, J Yue, L Meng… - Journal of Neural …, 2023 - iopscience.iop.org
Objective. Deep learning (DL) models have been proven to be effective in decoding motor
imagery (MI) signals in Electroencephalogram (EEG) data. However, DL models' success …

Riemannian geometric and ensemble learning for decoding cross-session motor imagery electroencephalography signals

L Pan, K Wang, L Xu, X Sun, W Yi, M Xu… - Journal of neural …, 2023 - iopscience.iop.org
Objective. Brain–computer interfaces (BCIs) enable a direct communication pathway
between the human brain and external devices, without relying on the traditional peripheral …

A high-speed hybrid brain-computer interface with more than 200 targets

J Han, M Xu, X **ao, W Yi, TP Jung… - Journal of Neural …, 2023 - iopscience.iop.org
Objective. Brain-computer interfaces (BCIs) have recently made significant strides in
expanding their instruction set, which has attracted wide attention from researchers. The …

A portable SSVEP-BCI system for rehabilitation exoskeleton in augmented reality environment

F Wang, Y Wen, J Bi, H Li, J Sun - Biomedical Signal Processing and …, 2023 - Elsevier
In order to strengthen the participation of stroke patients in rehabilitation training and
weaken the dependence of steady-state visually evoked potential (SSVEP)-based brain …

Improving AR-SSVEP recognition accuracy under high ambient brightness through iterative learning

R Zhang, L Cao, Z Xu, Y Zhang, L Zhang… - … on Neural Systems …, 2023 - ieeexplore.ieee.org
Augmented reality-based brain-computer interface (AR-BCI) system is one of the important
ways to promote BCI technology outside of the laboratory due to its portability and mobility …

Several inaccurate or erroneous conceptions and misleading propaganda about brain-computer interfaces

Y Chen, F Wang, T Li, L Zhao, A Gong… - Frontiers in Human …, 2024 - frontiersin.org
Brain-computer interface (BCI) is a revolutionizing human-computer interaction, which has
potential applications for specific individuals or groups in specific scenarios. Extensive …

[HTML][HTML] Cross-subject fusion based on time-weighting canonical correlation analysis in SSVEP-BCIs

Y Sun, W Ding, X Liu, D Zheng, X Chen, Q Hui, R Na… - Measurement, 2022 - Elsevier
Brain–computer interface technology provides new possibilities for medical rehabilitation
and human–computer interaction. The steady-state visual evoked potential based brain …