AIMC Topic: Brain-Computer Interfaces

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EEG-Deformer: A Dense Convolutional Transformer for Brain-Computer Interfaces.

IEEE journal of biomedical and health informatics Mar 6, 2025
Effectively learning the temporal dynamics in electroencephalogram (EEG) signals is challenging yet essential for decoding brain activities using brain-computer interfaces (BCIs). Although Transformers are popular for their long-term sequential learn...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Neural Networks, Computer Brain Young Adult Adult Male Electroencephalography Humans
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REI-Net: A Reference Electrode Standardization Interpolation Technique Based 3D CNN for Motor Imagery Classification.

IEEE journal of biomedical and health informatics Mar 6, 2025
High-quality scalp EEG datasets are extremely valuable for motor imagery (MI) analysis. However, due to electrode size and montage, different datasets inevitably experience channel information loss, posing a significant challenge for MI decoding. A 2...
Neural Networks, Computer Algorithms Adult Humans Electrodes Brain-Computer Interfaces Imagination Male Electroencephalography Signal Processing, Computer-Assisted
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Hybrid CNN-GRU Models for Improved EEG Motor Imagery Classification.

Sensors (Basel, Switzerland) Feb 25, 2025
Brain-computer interfaces (BCIs) based on electroencephalography (EEG) enable neural activity interpretation for device control, with motor imagery (MI) serving as a key paradigm for decoding imagined movements. Efficient feature extraction from raw ...
Movement Imagination Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Humans Neural Networks, Computer Algorithms
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Geometric neural network based on phase space for BCI-EEG decoding.

Journal of neural engineering Feb 19, 2025
The integration of Deep Learning (DL) algorithms on brain signal analysis is still in its nascent stages compared to their success in fields like Computer Vision. This is particularly true for Brain-computer interface (BCI), where the brain activity ...
Male Deep Learning Electroencephalography Neural Networks, Computer Algorithms Adult Brain-Computer Interfaces Humans
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Latent alignment in deep learning models for EEG decoding.

Journal of neural engineering Feb 17, 2025
. Brain-computer interfaces (BCIs) face a significant challenge due to variability in electroencephalography (EEG) signals across individuals. While recent approaches have focused on standardizing input signal distributions, we propose that aligning ...
Imagination Event-Related Potentials, P300 Sleep Stages Humans Deep Learning Female Electroencephalography Adult Male Brain-Computer Interfaces
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Enhancing detection of SSVEPs using discriminant compacted network.

Journal of neural engineering Feb 14, 2025
. Steady-state visual evoked potential-based brain-computer interfaces (SSVEP-BCIs) have gained significant attention due to their simplicity, high signal to noise ratio and high information transfer rates (ITRs). Currently, accurate detection is a c...
Female Adult Male Deep Learning Discriminant Analysis Electroencephalography Humans Neural Networks, Computer Brain-Computer Interfaces Evoked Potentials, Visual Photic Stimulation
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Depth-sensor-based shared control assistance for mobility and object manipulation: toward long-term home-use of BCI-controlled assistive robotic devices.

Journal of neural engineering Feb 14, 2025
Assistive robots can be developed to restore or provide more autonomy for individuals with motor impairments. In particular, power wheelchairs can compensate lower-limb impairments, while robotic manipulators can compensate upper-limbs impairments. R...
Self-Help Devices Quadriplegia Male Robotics Electroencephalography Equipment Design Brain-Computer Interfaces Wheelchairs Humans Female Adult
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A combination of deep learning models and type-2 fuzzy for EEG motor imagery classification through spatiotemporal-frequency features.

Journal of medical engineering & technology Feb 14, 2025
Developing a robust and effective technique is crucial for interpreting a user's brainwave signals accurately in the realm of biomedical signal processing. The variability and uncertainty present in EEG patterns over time, compounded by noise, pose n...
Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Deep Learning Fuzzy Logic Bayes Theorem Humans Algorithms
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BrainForest: Neuromorphic Multiplier-Less Bit-Serial Weight-Memory-Optimized 1024-Tree Brain-State Classification Processor.

IEEE transactions on biomedical circuits and systems Feb 11, 2025
Personalized brain implants have the potential to revolutionize the treatment of neurological disorders and augment cognition. Medical implants that deliver therapeutic stimulation in response to detected seizures have already been deployed for the t...
Machine Learning Algorithms Brain Humans Neural Networks, Computer Signal Processing, Computer-Assisted Brain-Computer Interfaces Models, Neurological Electroencephalography Seizures
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Multiclass Classification Framework of Motor Imagery EEG by Riemannian Geometry Networks.

IEEE journal of biomedical and health informatics Feb 10, 2025
In motor imagery (MI) tasks for brain computer interfaces (BCIs), the spatial covariance matrix (SCM) of electroencephalogram (EEG) signals plays a critical role in accurate classification. Given that SCMs are symmetric positive definite (SPD), Riema...
Brain Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces Imagination Humans Neural Networks, Computer Algorithms
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