AIMC Topic: Brain-Computer Interfaces
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Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer Interfaces.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 18, 2024
Training an accurate classifier for EEG-based brain-computer interface (BCI) requires EEG data from a large number of users, whereas protecting their data privacy is a critical consideration. Federated learning (FL) is a promising solution to this ch...
Effective Phoneme Decoding With Hyperbolic Neural Networks for High-Performance Speech BCIs.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 18, 2024
OBJECTIVE: Speech brain-computer interfaces (speech BCIs), which convert brain signals into spoken words or sentences, have demonstrated great potential for high-performance BCI communication. Phonemes are the basic pronunciation units. For monosylla...
Automatic Feature Selection for Sensorimotor Rhythms Brain-Computer Interface Fusing Expert and Data-Driven Knowledge.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 18, 2024
Early brain-computer interface (BCI) systems were mainly based on prior neurophysiological knowledge coupled with feedback training, while state-of-the-art interfaces rely on data-driven, machine learning (ML)-oriented methods. Despite the advances i...
Decoding Multi-Class Motor Imagery From Unilateral Limbs Using EEG Signals.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 17, 2024
The EEG is a widely utilized neural signal source, particularly in motor imagery-based brain-computer interface (MI-BCI), offering distinct advantages in applications like stroke rehabilitation. Current research predominantly concentrates on the bila...
A Strong and Simple Deep Learning Baseline for BCI Motor Imagery Decoding.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 16, 2024
We propose EEG-SimpleConv, a straightforward 1D convolutional neural network for Motor Imagery decoding in BCI. Our main motivation is to propose a simple and performing baseline that achieves high classification accuracy, using only standard ingredi...
A Spatio-Temporal Capsule Neural Network with Self-Correlation Routing for EEG Decoding of Semantic Concepts of Imagination and Perception Tasks.
Sensors (Basel, Switzerland)
Sep 15, 2024
Decoding semantic concepts for imagination and perception tasks (SCIP) is important for rehabilitation medicine as well as cognitive neuroscience. Electroencephalogram (EEG) is commonly used in the relevant fields, because it is a low-cost noninvasiv...
Research on shared control of robots based on hybrid brain-computer interface.
Journal of neuroscience methods
Sep 11, 2024
BACKGROUND: With the arrival of the new generation of artificial intelligence wave, new human-robot interaction technologies continue to emerge. Brain-computer interface (BCI) offers a pathway for state monitoring and interaction control between huma...
BELT: Bootstrapped EEG-to-Language Training by Natural Language Supervision.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 11, 2024
Decoding natural language from noninvasive brain signals has been an exciting topic with the potential to expand the applications of brain-computer interface (BCI) systems. However, current methods face limitations in decoding sentences from electroe...
Automatic Recognition of Multiple Emotional Classes from EEG Signals through the Use of Graph Theory and Convolutional Neural Networks.
Sensors (Basel, Switzerland)
Sep 10, 2024
Emotion is a complex state caused by the functioning of the human brain in relation to various events, for which there is no scientific definition. Emotion recognition is traditionally conducted by psychologists and experts based on facial expression...
Intelligent Control System for Brain-Controlled Mobile Robot Using Self-Learning Neuro-Fuzzy Approach.
Sensors (Basel, Switzerland)
Sep 10, 2024
Brain-computer interface (BCI) provides direct communication and control between the human brain and physical devices. It is achieved by converting EEG signals into control commands. Such interfaces have significantly improved the lives of disabled i...
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