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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 101110 of 466 papers

TitleStatusHype
Transfer Learning with Active Sampling for Rapid Training and Calibration in BCI-P300 Across Health States and Multi-centre Data0
Robust Feature Engineering Techniques for Designing Efficient Motor Imagery-Based BCI-Systems0
Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer InterfacesCode0
Channel Reflection: Knowledge-Driven Data Augmentation for EEG-Based Brain-Computer Interfaces0
Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer InterfacesCode0
Bi-Band ECoGNet for ECoG Decoding on Classification Task0
Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces0
ArEEG_Words: Dataset for Envisioned Speech Recognition using EEG for Arabic Words0
Decoding Imagined Movement in People with Multiple Sclerosis for Brain-Computer Interface Translation0
Dual Prototyping with Domain and Class Prototypes for Affective Brain-Computer Interface in Unseen Target Conditions0
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