AIMC Topic: Brain-Computer Interfaces

Clear Filters Showing 151 to 160 of 703 articles

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
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)
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
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
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)
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)
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...

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

Journal of neuroscience methods
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...

CTNet: a convolutional transformer network for EEG-based motor imagery classification.

Scientific reports
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...

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
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...

Bio-inspired EEG signal computing using machine learning and fuzzy theory for decision making in future-oriented brain-controlled vehicles.

SLAS technology
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...