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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 176–200 of 466 papers

TitleStatusHype
Brain Computer Interface Technology for Future Battlefield—0
EEG Cortical Source Feature based Hand Kinematics Decoding using Residual CNN-LSTM Neural Network—0
Brain Computer Interface: Deep Learning Approach to Predict Human Emotion Recognition—0
An Analysis of the Accuracy of the P300 BCI—0
EEGDnet: Fusing Non-Local and Local Self-Similarity for 1-D EEG Signal Denoising with 2-D Transformer—0
A case study on profiling of an EEG-based brain decoding interface on Cloud and Edge servers—0
EEG-GMACN: Interpretable EEG Graph Mutual Attention Convolutional Network—0
EEG-BBNet: a Hybrid Framework for Brain Biometric using Graph Connectivity—0
EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features—0
EEG-Based Speech Decoding: A Novel Approach Using Multi-Kernel Ensemble Diffusion Models—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
EEG-based Drowsiness Estimation for Driving Safety using Deep Q-Learning—0
Effects of Stimulus Type and of Error-Correcting Code Design on BCI Speller Performance—0
Brain-based control of car infotainment—0
An amplitudes-perturbation data augmentation method in convolutional neural networks for EEG decoding—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
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications—0
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