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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 311320 of 466 papers

TitleStatusHype
FOIT: Fast Online Instance Transfer for Improved EEG Emotion RecognitionCode0
BENDR: using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG dataCode1
EEG-Inception: An Accurate and Robust End-to-End Neural Network for EEG-based Motor Imagery ClassificationCode1
Online LDA based brain-computer interface system to aid disabled people0
Classification of fNIRS Data Under Uncertainty: A Bayesian Neural Network Approach0
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions0
4D Attention-based Neural Network for EEG Emotion Recognition0
Real or Virtual? Using Brain Activity Patterns to differentiate Attended Targets during Augmented Reality Scenarios0
In-Ear SpO2 for Classification of Cognitive Workload0
Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery FrameworkCode0
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