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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

Showing 151175 of 466 papers

TitleStatusHype
Precision Enhancement in Sustained Visual Attention Training Platforms: Offline EEG Signal Analysis for Classifier Fine-Tuning0
EEG2TEXT: Open Vocabulary EEG-to-Text Decoding with EEG Pre-Training and Multi-View Transformer0
Quantifying Spatial Domain Explanations in BCI using Earth Mover's DistanceCode0
Unveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Text0
Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization0
Evaluating Fast Adaptability of Neural Networks for Brain-Computer InterfaceCode0
Psychometry: An Omnifit Model for Image Reconstruction from Human Brain Activity0
MindArm: Mechanized Intelligent Non-Invasive Neuro-Driven Prosthetic Arm System0
Transferring BCI models from calibration to control: Observing shifts in EEG features0
Uncertainty Quantification for cross-subject Motor Imagery classificationCode0
Geometric Neural Network based on Phase Space for BCI-EEG decodingCode0
Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets0
Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification0
FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network0
Stimulation technology for brain and nerves, now and future0
Towards Decoding Brain Activity During Passive Listening of SpeechCode0
ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for Arabic Characters0
Early feasibility of an embedded bi-directional brain-computer interface for ambulation0
Classification of Emerging Neural Activity from Planning to Grasp Execution using a Novel EEG-Based BCI Platform0
Stimulus-Informed Generalized Canonical Correlation Analysis for Group Analysis of Neural Responses to Natural StimuliCode0
Wavelet Analysis of Noninvasive EEG Signals Discriminates Complex and Natural Grasp Types0
Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification0
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding0
Using i-vectors for subject-independent cross-session EEG transfer learning0
A Temporal-Spectral Fusion Transformer with Subject-Specific Adapter for Enhancing RSVP-BCI DecodingCode0
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