AIMC Topic: Brain-Computer Interfaces

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Classification of hand movements from EEG using a FusionNet based LSTM network.

Journal of neural engineering Nov 20, 2024
. Accurate classification of electroencephalogram (EEG) signals is crucial for advancing brain-computer interface (BCI) technology. However, current methods face significant challenges in classifying hand movement EEG signals, including effective spa...
Movement Electroencephalography Hand Brain-Computer Interfaces Humans Neural Networks, Computer
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Enhancing Motor Imagery Classification with Residual Graph Convolutional Networks and Multi-Feature Fusion.

International journal of neural systems Nov 19, 2024
Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoption of motor imagery (MI)-based brain-computer interface (BCI) systems in stroke rehabilitation. However, analyzing electroencephalogram (EEG) signals f...
Stroke Rehabilitation Imagination Male Signal Processing, Computer-Assisted Humans Female Stroke Middle Aged Neural Networks, Computer Aged Brain-Computer Interfaces Brain Electroencephalography Adult
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Partial prior transfer learning based on self-attention CNN for EEG decoding in stroke patients.

Scientific reports Nov 15, 2024
The utilization of motor imagery-based brain-computer interfaces (MI-BCI) has been shown to assist stroke patients activate motor regions in the brain. In particular, the brain regions activated by unilateral upper limb multi-task are more extensive,...
Adult Male Middle Aged Electroencephalography Stroke Stroke Rehabilitation Machine Learning Brain-Computer Interfaces Algorithms Female Humans Neural Networks, Computer
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A hybrid local-global neural network for visual classification using raw EEG signals.

Scientific reports Nov 8, 2024
EEG-based brain-computer interfaces (BCIs) have the potential to decode visual information. Recently, artificial neural networks (ANNs) have been used to classify EEG signals evoked by visual stimuli. However, methods using ANNs to extract features f...
Brain-Computer Interfaces Photic Stimulation Humans Neural Networks, Computer Algorithms Electroencephalography Signal Processing, Computer-Assisted
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Decoding multi-limb movements from two-photon calcium imaging of neuronal activity using deep learning.

Journal of neural engineering Nov 7, 2024
Brain-machine interfaces (BMIs) aim to restore sensorimotor function to individuals suffering from neural injury and disease. A critical step in implementing a BMI is to decode movement intention from recorded neural activity patterns in sensorimotor...
Mice, Inbred C57BL Neurons Calcium Brain-Computer Interfaces Movement Extremities Male Deep Learning Mice Animals
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Classification of EEG evoked in 2D and 3D virtual reality: traditional machine learning versus deep learning.

Biomedical physics & engineering express Nov 5, 2024
. Virtual reality (VR) simulates real-life events and scenarios and is widely utilized in education, entertainment, and medicine. VR can be presented in two dimensions (2D) or three dimensions (3D), with 3D VR offering a more realistic and immersive ...
Neural Networks, Computer Machine Learning Algorithms Humans Virtual Reality Adult Brain-Computer Interfaces Brain Support Vector Machine Male Female Electroencephalography Deep Learning Young Adult
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Task-oriented EEG denoising generative adversarial network for enhancing SSVEP-BCI performance.

Journal of neural engineering Nov 5, 2024
The quality of electroencephalogram (EEG) signals directly impacts the performance of brain-computer interface (BCI) tasks. Many methods have been proposed to eliminate noise from EEG signals, but most of these methods focus solely on signal denoisin...
Male Electroencephalography Brain-Computer Interfaces Female Young Adult Adult Evoked Potentials, Visual Signal-To-Noise Ratio Photic Stimulation Humans Neural Networks, Computer
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Design of EEG based thought identification system using EMD & deep neural network.

Scientific reports Nov 4, 2024
Biological communication system for neurological disorder patients is similar to the Brain Computer Interface in a way that it facilitates the connection to the outside world in real time. The interdisciplinary field of Electroencephalogram based mes...
Brain Deep Learning Electroencephalography Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Brain-Computer Interfaces
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A protocol for trustworthy EEG decoding with neural networks.

Neural networks : the official journal of the International Neural Network Society Nov 2, 2024
Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performance on a variety of decoding tasks. Despite their high performance, existing solutions do not fully address the challenge posed by the introduction of m...
Neural Networks, Computer Algorithms Imagination Brain Humans Electroencephalography Brain-Computer Interfaces Event-Related Potentials, P300 Adult Male Deep Learning
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Review of deep representation learning techniques for brain-computer interfaces.

Journal of neural engineering Nov 1, 2024
In the field of brain-computer interfaces (BCIs), the potential for leveraging deep learning techniques for representing electroencephalogram (EEG) signals has gained substantial interest.: This review synthesizes empirical findings from a collection...
Humans Deep Learning Electroencephalography Brain-Computer Interfaces
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