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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 201–225 of 466 papers

TitleStatusHype
Calibration-Free Driver Drowsiness Classification based on Manifold-Level AugmentationCode0
Hybrid Paradigm-based Brain-Computer Interface for Robotic Arm Control—0
CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals—0
Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals—0
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network—0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
Closed loop BCI System for Cybathlon 2020Code1
Target-centered Subject Transfer Framework for EEG Data Augmentation—0
Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition—0
Brain informed transfer learning for categorizing construction hazards—0
Motor imagery classification using EEG spectrograms—0
Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision DecodingCode2
Towards Fast Single-Trial Online ERP based Brain-Computer Interface using dry EEG electrodes and neural networks: a pilot studyCode0
Embedding neurophysiological signalsCode0
Stimulus-Informed Generalized Canonical Correlation Analysis of Stimulus-Following Brain ResponsesCode0
FingerFlex: Inferring Finger Trajectories from ECoG signalsCode1
Toward the application of XAI methods in EEG-based systems—0
A Transformer-based deep neural network model for SSVEP classificationCode1
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features—0
In the realm of hybrid Brain: Human Brain and AI—0
On The Effects Of Data Normalisation For Domain Adaptation On EEG Data—0
Cross Task Neural Architecture Search for EEG Signal ClassificationsCode1
Mental arithmetic task classification with convolutional neural network based on spectral-temporal features from EEG—0
A Novel Semi-supervised Meta Learning Method for Subject-transfer Brain-computer Interface—0
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