AIMC Topic: Brain-Computer Interfaces

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Data augmentation using masked principal component representation for deep learning-based SSVEP-BCIs.

Journal of neural engineering May 28, 2025
Data augmentation has been demonstrated to improve the classification accuracy of deep learning models in steady-state visual evoked potential-based brain-computer interfaces (BCIs), particularly when dealing with limited electroencephalography (EEG)...
Humans Adult Male Brain-Computer Interfaces Evoked Potentials, Visual Photic Stimulation Deep Learning Principal Component Analysis Electroencephalography
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Metaplasticity and continual learning: mechanisms subserving brain computer interface proficiency.

Journal of neural engineering May 23, 2025
Brain computer interfaces (BCIs) require substantial cognitive flexibility to optimize control performance. Remarkably, learning this control is rapid, suggesting it might be mediated by neuroplasticity mechanisms operating on very short time scales....
Models, Neurological Learning Male Mice, Inbred C57BL Brain-Computer Interfaces Animals Mice Mice, Transgenic Neuronal Plasticity Optogenetics
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Enhanced EEG Forecasting: A Probabilistic Deep Learning Approach.

Neural computation Mar 18, 2025
Forecasting electroencephalography (EEG) signals, that is, estimating future values of the time series based on the past ones, is essential in many real-time EEG-based applications, such as brain-computer interfaces and closed-loop brain stimulation....
Electroencephalography Brain-Computer Interfaces Humans Neural Networks, Computer Forecasting Brain Deep Learning
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[Three-dimensional convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery electroencephalography signal].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2024
The brain-computer interface (BCI) based on motor imagery electroencephalography (EEG) shows great potential in neurorehabilitation due to its non-invasive nature and ease of use. However, motor imagery EEG signals have low signal-to-noise ratios and...
Humans Neural Networks, Computer Brain Signal Processing, Computer-Assisted Brain-Computer Interfaces Convolutional Neural Networks Imagination Electroencephalography
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[The supernumerary robotic limbs of brain-computer interface based on asynchronous steady-state visual evoked potential].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Aug 25, 2024
Brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) have attracted much attention in the field of intelligent robotics. Traditional SSVEP-based BCI systems mostly use synchronized triggers without identifying whether ...
Discriminant Analysis Electroencephalography Brain-Computer Interfaces Evoked Potentials, Visual Humans Algorithms Robotics
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EEG-Based Feature Classification Combining 3D-Convolutional Neural Networks with Generative Adversarial Networks for Motor Imagery.

Journal of integrative neuroscience Aug 20, 2024
BACKGROUND: The adoption of convolutional neural networks (CNNs) for decoding electroencephalogram (EEG)-based motor imagery (MI) in brain-computer interfaces has significantly increased recently. The effective extraction of motor imagery features is...
Adult Electroencephalography Signal Processing, Computer-Assisted Neural Networks, Computer Brain Brain-Computer Interfaces Motor Activity Imagination Humans
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Domain-Incremental Learning Framework for Continual Motor Imagery EEG Classification Task.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Due to inter-subject variability in electroencephalogram (EEG) signals, the generalization ability of many existing brain-computer interface (BCI) models is significantly limited. Although transfer learning (TL) offers a temporary solution, in scenar...
Algorithms Electroencephalography Signal Processing, Computer-Assisted Humans Machine Learning Brain-Computer Interfaces Imagination
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Baseline-Guided Representation Learning for Noise-Robust EEG Signal Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Brain-computer interfaces (BCIs) suffer from limited accuracy due to noisy electroencephalography (EEG) signals. Existing denoising methods often remove artifacts such as eye movement or use techniques such as linear detrending, which inadvertently d...
Brain-Computer Interfaces Signal-To-Noise Ratio Electroencephalography Signal Processing, Computer-Assisted Machine Learning Algorithms Humans Deep Learning
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Enhancement of Functional Connectivity in Frontal-Parietal Regions After BCI-Actuated Supernumerary Robotic Finger Training.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
The supernumerary robotic finger (SRF) can expand human hand abilities to achieve motor augmentation, and integrate with brain computer interface (BCI) to free the occupation of inherent body degrees of freedom. However, the neuro remodeling mechanis...
Female Young Adult Adult Male Magnetic Resonance Imaging Humans Fingers Frontal Lobe Parietal Lobe Robotics Brain-Computer Interfaces
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EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Electroencephalogram (EEG) is a valuable technique to record brain electrical activity through electrodes placed on the scalp. Analyzing EEG signals contributes to the understanding of neurological conditions and developing brain-computer interface. ...
Electrodes Humans Brain-Computer Interfaces Neural Networks, Computer Algorithms Brain Electroencephalography Signal Processing, Computer-Assisted
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