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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 301310 of 466 papers

TitleStatusHype
Toward asynchronous EEG-based BCI: Detecting imagined words segments in continuous EEG signalsCode0
Source Aware Deep Learning Framework for Hand Kinematic Reconstruction using EEG Signal0
Classification of Motor Imagery EEG Signals by Using a Divergence Based Convolutional Neural NetworkCode0
FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer InterfaceCode1
A New Method for Features Normalization in Motor Imagery Few-Shot Learning using Resting-State0
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding0
Real Time Vigilance Detection using Frontal EEG0
EmoWrite: A Sentiment Analysis-Based Thought to Text Conversion -- A Validation Study0
Decoding Event-related Potential from Ear-EEG Signals based on Ensemble Convolutional Neural Networks in Ambulatory Environment0
Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface0
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