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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 …
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 …
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 …
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 …
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 …
Transformative deep neural network approaches in kidney ultrasound segmentation: empirical validation with an annotated dataset
R Khan, C **ao, Y Liu, J Tian, Z Chen, L Su… - Interdisciplinary …, 2024 - Springer
Kidney ultrasound (US) images are primarily employed for diagnosing different renal
diseases. Among them, one is renal localization and detection, which can be carried out by …
diseases. Among them, one is renal localization and detection, which can be carried out by …
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 …
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 …