A high-speed hybrid brain-computer interface with more than 200 targets
Objective. Brain-computer interfaces (BCIs) have recently made significant strides in
expanding their instruction set, which has attracted wide attention from researchers. The …
expanding their instruction set, which has attracted wide attention from researchers. The …
Inter-participant transfer learning with attention based domain adversarial training for P300 detection
A Brain-computer interface (BCI) system establishes a novel communication channel
between the human brain and a computer. Most event related potential-based BCI …
between the human brain and a computer. Most event related potential-based BCI …
Upregulation of p300 in paclitaxel-resistant TNBC: implications for cell proliferation via the PCK1/AMPK axis
PW Zhao, JX Cui, XM Wang - The Pharmacogenomics Journal, 2024 - nature.com
Objective To explore the role of p300 in the context of paclitaxel (PTX) resistance in triple-
negative breast cancer (TNBC) cells, focusing on its interaction with the …
negative breast cancer (TNBC) cells, focusing on its interaction with the …
Self-distillation with beta label smoothing-based cross-subject transfer learning for P300 classification
Background: The P300 speller is one of the most well-known brain-computer interface (BCI)
systems, offering users a novel way to communicate with their environment by decoding …
systems, offering users a novel way to communicate with their environment by decoding …
A novel command generation method for SSVEP-based BCI by introducing SSVEP blocking response
X Yuan, L Zhang, Q Sun, X Lin, C Li - Computers in Biology and Medicine, 2022 - Elsevier
Increasing the number of commands in a steady-state visual evoked potential (SSVEP)-
based brain-computer interface (BCI) by increasing the number of visual stimuli has been …
based brain-computer interface (BCI) by increasing the number of visual stimuli has been …
MOCNN: A Multiscale Deep Convolutional Neural Network for ERP-Based Brain-Computer Interfaces
Event-related potentials (ERPs) reflect neurophysiological changes of the brain in response
to external events and their associated underlying complex spatiotemporal feature …
to external events and their associated underlying complex spatiotemporal feature …
Cross Stimulus Transfer Learning Framework Using Common Period Repetition Components for Fast Calibration of SSVEP Based BCIs
J **, X He, R Xu, R Zhao, X Long… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
The decoding approach of steady-state visual evoked potentials (SSVEP) based on
supervised learning have achieved remarkable results. However, these approaches require …
supervised learning have achieved remarkable results. However, these approaches require …
[HTML][HTML] Hybrid SSVEP+ P300 brain-computer interface can deal with non-stationary cerebral responses with the use of adaptive classification
DD Kapgate - Journal of Neurorestoratology, 2024 - Elsevier
Introduction The non-stationarity of electroencephalograms (EEG) has a substantial effect on
the performance of classifiers in brain-computer interface (BCI) systems. To tackle this …
the performance of classifiers in brain-computer interface (BCI) systems. To tackle this …
Decoding continuous motion trajectories of upper limb from EEG signals based on feature selection and nonlinear methods
Objective. Brain–computer interface (BCI) system has emerged as a promising technology
that provides direct communication and control between the human brain and external …
that provides direct communication and control between the human brain and external …
Spatio-temporal matched filter adjustment for enhanced accuracy in brain responses classification
In this paper, we apply modified spatio-temporal matched filtering (MSTMF) to enhance
electroencephalographic (EEG) signals in evoked potentials (EP) based brain–computer …
electroencephalographic (EEG) signals in evoked potentials (EP) based brain–computer …