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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 151–200 of 466 papers

TitleStatusHype
Detecting Driver's Distraction using Long-term Recurrent Convolutional Network—0
Adaptive neural network classifier for decoding MEG signals—0
Deep Transfer Learning for EEG-based Brain Computer Interface—0
Bayesian Nonparametric Models for Synchronous Brain-Computer Interfaces—0
An Accurate EEGNet-based Motor-Imagery Brain-Computer Interface for Low-Power Edge Computing—0
Deep Learning in fNIRS: A review—0
DGAFF: Deep Genetic Algorithm Fitness Formation for EEG Bio-Signal Channel Selection—0
Deep Learning in EEG: Advance of the Last Ten-Year Critical Period—0
Bayesian Networks for Brain-Computer Interfaces: A Survey—0
A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition—0
Evaluation of Classical Features and Classifiers in Brain-Computer Interface Tasks—0
Easing Seasickness through Attention Redirection with a Mindfulness-Based Brain--Computer Interface—0
Edge-Fog Computing-Enabled EEG Data Compression via Asymmetrical Variational Discrete Cosine Transform Network—0
EEG2GAIT: A Hierarchical Graph Convolutional Network for EEG-based Gait Decoding—0
EEG2TEXT: Open Vocabulary EEG-to-Text Decoding with EEG Pre-Training and Multi-View Transformer—0
EEG-assisted Modulation of Sound Sources in the Auditory Scene—0
EEG-based 90-Degree Turn Intention Detection for Brain-Computer Interface—0
EEG-based AI-BCI Wheelchair Advancement: A Brain-Computer Interfacing Wheelchair System Using Deep Learning Approach—0
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications—0
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning—0
EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models—0
Deep learning for ECoG brain-computer interface: end-to-end vs. hand-crafted features—0
EEG-BBNet: a Hybrid Framework for Brain Biometric using Graph Connectivity—0
Deep Learning Decoding of Mental State in Non-invasive Brain Computer Interface—0
Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button—0
Brain Computer Interface Technology for Future Battlefield—0
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks—0
Brain-Computer Interface with Corrupted EEG Data: A Tensor Completion Approach—0
EEGDnet: Fusing Non-Local and Local Self-Similarity for 1-D EEG Signal Denoising with 2-D Transformer—0
Deep learning-based classification of fine hand movements from low frequency EEG—0
EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network—0
Deep Learning Architecture for Motor Imaged Words—0
Autoregressive models for biomedical signal processing—0
A Multi-Context Character Prediction Model for a Brain-Computer Interface—0
EEG-NeXt: A Modernized ConvNet for The Classification of Cognitive Activity from EEG—0
EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units—0
EEG Right & Left Voluntary Hand Movement-based Virtual Brain-Computer Interfacing Keyboard Using Hybrid Deep Learning Approach—0
Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI—0
Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance—0
Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition—0
A neuro-inspired system for online learning and recognition of parallel spike trains, based on spike latency and heterosynaptic STDP—0
Emotion-Agent: Unsupervised Deep Reinforcement Learning with Distribution-Prototype Reward for Continuous Emotional EEG Analysis—0
EmoWrite: A Sentiment Analysis-Based Thought to Text Conversion -- A Validation Study—0
End-to-end translation of human neural activity to speech with a dual-dual generative adversarial network—0
Enhanced Generative Adversarial Networks for Unseen Word Generation from EEG Signals—0
Enhanced motor imagery-based EEG classification using a discriminative graph Fourier subspace—0
Enhancing EEG Signal Generation through a Hybrid Approach Integrating Reinforcement Learning and Diffusion Models—0
Ensemble Classifier for Eye State Classification using EEG Signals—0
Automatic Muscle Artifacts Identification and Removal from Single-Channel EEG Using Wavelet Transform with Meta-heuristically Optimized Non-local Means Filter—0
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