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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 351–375 of 466 papers

TitleStatusHype
Voxel selection framework based on meta-heuristic search and mutual information for brain decoding—0
Wavelet Analysis of Noninvasive EEG Signals Discriminates Complex and Natural Grasp Types—0
Wheelchair automation by a hybrid BCI system using SSVEP and eye blinks—0
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
Zydeco-Style Spike Sorting Low Power VLSI Architecture for IoT BCI Implants—0
Covariance Density Neural Networks—0
The 2025 PNPL Competition: Speech Detection and Phoneme Classification in the LibriBrain Dataset—0
3D-CLMI: A Motor Imagery EEG Classification Model via Fusion of 3D-CNN and LSTM with Attention—0
4D Attention-based Neural Network for EEG Emotion Recognition—0
A 6.3-Nanowatt-per-Channel 96-Channel Neural Spike Processor for a Movement-Intention-Decoding Brain-Computer-Interface Implant—0
A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition—0
AbsoluteNet: A Deep Learning Neural Network to Classify Cerebral Hemodynamic Responses of Auditory Processing—0
A case study on profiling of an EEG-based brain decoding interface on Cloud and Edge servers—0
A3E: Aligned and Augmented Adversarial Ensemble for Accurate, Robust and Privacy-Preserving EEG Decoding—0
A Computationally Efficient Multiclass Time-Frequency Common Spatial Pattern Analysis on EEG Motor Imagery—0
A Consumer BCI for Automated Music Evaluation Within a Popular On-Demand Music Streaming Service - Taking Listener's Brainwaves to Extremes—0
A Convolutional Network Adaptation for Cortical Classification During Mobile Brain Imaging—0
Acting Thoughts: Towards a Mobile Robotic Service Assistant for Users with Limited Communication Skills—0
Active recursive Bayesian inference using Rényi information measures—0
Active Semi-supervised Transfer Learning (ASTL) for Offline BCI Calibration—0
Adaptive neural network classifier for decoding MEG signals—0
Advancing Brain-Computer Interface System Performance in Hand Trajectory Estimation with NeuroKinect—0
A Dynamic Domain Adaptation Deep Learning Network for EEG-based Motor Imagery Classification—0
A GA-based feature selection of the EEG signals by classification evaluation: Application in BCI systems—0
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