AIMC Topic: Brain-Computer Interfaces

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Cross-subject emotion recognition in brain-computer interface based on frequency band attention graph convolutional adversarial neural networks.

Journal of neuroscience methods Sep 3, 2024
BACKGROUND: Emotion is an important area in neuroscience. Cross-subject emotion recognition based on electroencephalogram (EEG) data is challenging due to physiological differences between subjects. Domain gap, which refers to the different distribut...
Humans Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Neural Networks, Computer Brain Emotions
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CTNet: a convolutional transformer network for EEG-based motor imagery classification.

Scientific reports Aug 30, 2024
Brain-computer interface (BCI) technology bridges the direct communication between the brain and machines, unlocking new possibilities for human interaction and rehabilitation. EEG-based motor imagery (MI) plays a pivotal role in BCI, enabling the tr...
Algorithms Humans Brain Signal Processing, Computer-Assisted Neural Networks, Computer Electroencephalography Brain-Computer Interfaces Imagination
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Improving classification performance of motor imagery BCI through EEG data augmentation with conditional generative adversarial networks.

Neural networks : the official journal of the International Neural Network Society Aug 28, 2024
In brain-computer interface (BCI), building accurate electroencephalogram (EEG) classifiers for specific mental tasks is critical for BCI performance. The classifiers are developed by machine learning (ML) and deep learning (DL) techniques, requiring...
Brain-Computer Interfaces Imagination Brain Deep Learning Electroencephalography Neural Networks, Computer Humans Machine Learning
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Bio-inspired EEG signal computing using machine learning and fuzzy theory for decision making in future-oriented brain-controlled vehicles.

SLAS technology Aug 28, 2024
One kind of autonomous vehicle that can take instructions from the driver by reading their electroencephalogram (EEG) signals using a Brain-Computer Interface (BCI) is called a Brain-Controlled Vehicle (BCV). The operation of such a vehicle is greatl...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Fuzzy Logic Decision Making Electroencephalography Humans Machine Learning
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Advanced rehabilitation in ischaemic stroke research.

Stroke and vascular neurology Aug 27, 2024
At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke, the mortality of patients has been greatly reduced but the number of disabled survivors is increasing, and most of them are elderly patients. Physic...
Humans Physical Therapy Modalities Animals Stroke Rehabilitation Treatment Outcome Ischemic Stroke Brain-Computer Interfaces Disease Models, Animal Recovery of Function Robotics
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MOCNN: A Multiscale Deep Convolutional Neural Network for ERP-Based Brain-Computer Interfaces.

IEEE transactions on cybernetics Aug 26, 2024
Event-related potentials (ERPs) reflect neurophysiological changes of the brain in response to external events and their associated underlying complex spatiotemporal feature information is governed by ongoing oscillatory activity within the brain. De...
Neural Networks, Computer Algorithms Brain Humans Signal Processing, Computer-Assisted Brain-Computer Interfaces Evoked Potentials Deep Learning Electroencephalography
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Online Privacy-Preserving EEG Classification by Source-Free Transfer Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Aug 26, 2024
Electroencephalogram (EEG) signals play an important role in brain-computer interface (BCI) applications. Recent studies have utilized transfer learning to assist the learning task in the new subject, i.e., target domain, by leveraging beneficial inf...
Algorithms Adult Online Systems Electroencephalography Male Transfer, Psychology Humans Privacy Machine Learning Brain-Computer Interfaces
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Simultaneous EEG-fNIRS Data Classification Through Selective Channel Representation and Spectrogram Imaging.

IEEE journal of translational engineering in health and medicine Aug 23, 2024
The integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) can facilitate the advancement of brain-computer interfaces (BCIs). However, existing research in this domain has grappled with the challenge of the eff...
Spectroscopy, Near-Infrared Electroencephalography Female Humans Deep Learning Adult Signal Processing, Computer-Assisted Brain Male Brain-Computer Interfaces
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Inter-participant transfer learning with attention based domain adversarial training for P300 detection.

Neural networks : the official journal of the International Neural Network Society Aug 22, 2024
A Brain-computer interface (BCI) system establishes a novel communication channel between the human brain and a computer. Most event related potential-based BCI applications make use of decoding models, which requires training. This training process ...
Humans Event-Related Potentials, P300 Neural Networks, Computer Attention Deep Learning Brain-Computer Interfaces Electroencephalography
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SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection.

Neural networks : the official journal of the International Neural Network Society Aug 22, 2024
Emotional recognition is highly important in the field of brain-computer interfaces (BCIs). However, due to the individual variability in electroencephalogram (EEG) signals and the challenges in obtaining accurate emotional labels, traditional method...
Electroencephalography Supervised Machine Learning Attention Male Emotions Consciousness Brain-Computer Interfaces Humans Neural Networks, Computer Female Adult
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