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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 251260 of 466 papers

TitleStatusHype
Zydeco-Style Spike Sorting Low Power VLSI Architecture for IoT BCI Implants0
Classification of Electroencephalograms during Mathematical Calculations Using Deep Learning0
EEG-BBNet: a Hybrid Framework for Brain Biometric using Graph Connectivity0
An intertwined neural network model for EEG classification in brain-computer interfaces0
How does artificial intelligence contribute to iEEG research?0
Factorization Approach for Sparse Spatio-Temporal Brain-Computer Interface0
EPOC Emotiv EEG Basics0
Interaction-Grounded Learning with Action-inclusive Feedback0
A Neural-Inspired Architecture for EEG-Based Auditory Attention Detection0
Classification of EEG Motor Imagery Using Deep Learning for Brain-Computer Interface Systems0
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