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Brain Computer Interface

A Brain-Computer Interface (BCI), also known as a Brain-Machine Interface (BMI), is a technology that enables direct communication between the brain and an external device, such as a computer or a machine, without the need for any muscular or peripheral nerve activity. Essentially, BCIs establish a direct pathway between the brain and an external device, allowing for bidirectional communication.

BCIs typically work by detecting and interpreting brain signals, which are then translated into commands that control external devices or provide feedback to the user. These brain signals can be detected through various methods, including electroencephalography (EEG), which measures electrical activity in the brain through electrodes placed on the scalp, or invasive techniques such as implanted electrodes.

Papers

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Showing 301–325 of 466 papers

TitleStatusHype
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback—0
Domain Adaptation with Optimal Transport on the Manifold of SPD matrices—0
In-Ear SpO2 for Classification of Cognitive Workload—0
Information Theoretic Feature Transformation Learning for Brain Interfaces—0
Integrating Biological and Machine Intelligence: Attention Mechanisms in Brain-Computer Interfaces—0
Integrating Language-Image Prior into EEG Decoding for Cross-Task Zero-Calibration RSVP-BCI—0
Interaction-Grounded Learning with Action-inclusive Feedback—0
Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification—0
Interpretable Dual-Filter Fuzzy Neural Networks for Affective Brain-Computer Interfaces—0
Inter-stimulus Interval Study for the Tactile Point-pressure Brain-computer Interface—0
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding—0
Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface—0
In the realm of hybrid Brain: Human Brain and AI—0
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition—0
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks—0
Is controlling a brain-computer interface just a matter of presence of mind? The limits of cognitive-motor dissociation—0
JNEEG shield for Jetson Nano for real-time EEG signal processing with deep learning—0
Kullback-Leibler Penalized Sparse Discriminant Analysis for Event-Related Potential Classification—0
Learning from Label Proportions in Brain-Computer Interfaces: Online Unsupervised Learning with Guarantees—0
Learning Patterns in Imaginary Vowels for an Intelligent Brain Computer Interface (BCI) Design—0
Learning shared neural manifolds from multi-subject FMRI data—0
Light-Weight 1-D Convolutional Neural Network Architecture for Mental Task Identification and Classification Based on Single-Channel EEG—0
Low count of optically pumped magnetometers furnishes a reliable real-time access to sensorimotor rhythm—0
L-Sort: An Efficient Hardware for Real-time Multi-channel Spike Sorting with Localization—0
Measuring the functional connectome "on-the-fly": towards a new control signal for fMRI-based brain-computer interfaces—0
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