AIMC Topic: Brain-Computer Interfaces

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EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning.

Journal of neuroscience methods Jul 3, 2024
Brain-computer interface (BCI) technology holds promise for individuals with profound motor impairments, offering the potential for communication and control. Motor imagery (MI)-based BCI systems are particularly relevant in this context. Despite the...
Imagination Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans Algorithms Brain Deep Learning
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A Method to Extract Task-Related EEG Feature Based on Lightweight Convolutional Neural Network.

Neuroscience bulletin Jul 2, 2024
Unlocking task-related EEG spectra is crucial for neuroscience. Traditional convolutional neural networks (CNNs) effectively extract these features but face limitations like overfitting due to small datasets. To address this issue, we propose a light...
Humans Neural Networks, Computer Adult Male Electroencephalography Brain Female Young Adult Signal Processing, Computer-Assisted Brain-Computer Interfaces
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Hybrid Brain-Computer Interface Controlled Soft Robotic Glove for Stroke Rehabilitation.

IEEE journal of biomedical and health informatics Jul 2, 2024
Soft robotic glove controlled by a brain-computer interface (BCI) have demonstrated effectiveness in hand rehabilitation for stroke patients. Current systems rely on static visual representations for patients to perform motor imagination (MI) tasks, ...
Stroke Brain-Computer Interfaces Evoked Potentials, Visual Equipment Design Young Adult Middle Aged Signal Processing, Computer-Assisted Adult Robotics Algorithms Hand Male Electroencephalography Female Stroke Rehabilitation Aged Humans
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Unsupervised and semi-supervised domain adaptation networks considering both global knowledge and prototype-based local class information for Motor Imagery Classification.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2024
The non-stationarity of EEG signals results in variability across sessions, impeding model building and data sharing. In this paper, we propose a domain adaptation method called GPL, which simultaneously considers global knowledge and prototype-based...
Brain-Computer Interfaces Imagination Unsupervised Machine Learning Electroencephalography Supervised Machine Learning Algorithms Brain Humans Neural Networks, Computer
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Speech decoding from stereo-electroencephalography (sEEG) signals using advanced deep learning methods.

Journal of neural engineering Jun 27, 2024
Brain-computer interfaces (BCIs) are technologies that bypass damaged or disrupted neural pathways and directly decode brain signals to perform intended actions. BCIs for speech have the potential to restore communication by decoding the intended spe...
Speech Electroencephalography Epilepsy Brain-Computer Interfaces Stereotaxic Techniques Adult Male Humans Deep Learning Neural Networks, Computer Female
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STaRNet: A spatio-temporal and Riemannian network for high-performance motor imagery decoding.

Neural networks : the official journal of the International Neural Network Society Jun 26, 2024
Brain-computer interfaces (BCIs), representing a transformative form of human-computer interaction, empower users to interact directly with external environments through brain signals. In response to the demands for high accuracy, robustness, and end...
Movement Imagination Brain Humans Electroencephalography Neural Networks, Computer Brain-Computer Interfaces
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A novel virtual robotic platform for controlling six degrees of freedom assistive devices with body-machine interfaces.

Computers in biology and medicine Jun 25, 2024
Body-machine interfaces (BoMIs)-systems that control assistive devices (e.g., a robotic manipulator) with a person's movements-offer a robust and non-invasive alternative to brain-machine interfaces for individuals with neurological injuries. However...
Humans Female Adult Brain-Computer Interfaces Male User-Computer Interface Self-Help Devices Robotics
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Use of Artificial Intelligence Techniques to Assist Individuals with Physical Disabilities.

Annual review of biomedical engineering Jun 20, 2024
Assistive technologies (AT) enable people with disabilities to perform activities of daily living more independently, have greater access to community and healthcare services, and be more productive performing educational and/or employment tasks. Int...
Humans Activities of Daily Living Brain-Computer Interfaces Exoskeleton Device Persons with Disabilities Self-Help Devices Artificial Intelligence Robotics Software Natural Language Processing User-Computer Interface
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Multiclass Classification of Visual Electroencephalogram Based on Channel Selection, Minimum Norm Estimation Algorithm, and Deep Network Architectures.

Sensors (Basel, Switzerland) Jun 19, 2024
This work addresses the challenge of classifying multiclass visual EEG signals into 40 classes for brain-computer interface applications using deep learning architectures. The visual multiclass classification approach offers BCI applications a signif...
Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans Neural Networks, Computer Algorithms Deep Learning
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Large-scale foundation models and generative AI for BigData neuroscience.

Neuroscience research Jun 17, 2024
Recent advances in machine learning have led to revolutionary breakthroughs in computer games, image and natural language understanding, and scientific discovery. Foundation models and large-scale language models (LLMs) have recently achieved human-l...
Machine Learning Brain-Computer Interfaces Neurosciences Humans Artificial Intelligence
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