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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 341350 of 466 papers

TitleStatusHype
Hybrid Template Canonical Correlation Analysis Method for Enhancing SSVEP Recognition under data-limited Condition0
Selection of Proper EEG Channels for Subject Intention Classification Using Deep Learning0
GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery SignalsCode2
Classification and Recognition of Encrypted EEG Data Neural Network0
Constrained Variational Autoencoder for improving EEG based Speech Recognition Systems0
PhyAAt: Physiology of Auditory Attention to Speech DatasetCode0
Mu-suppression detection in motor imagery electroencephalographic signals using the generalized extreme value distribution0
Attention Patterns Detection using Brain Computer Interfaces0
Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI0
Classification of Visual Perception and Imagery based EEG Signals Using Convolutional Neural Networks0
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