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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 391400 of 466 papers

TitleStatusHype
An Ensemble Learning Based Classification of Individual Finger Movement from EEG0
A Neural-Inspired Architecture for EEG-Based Auditory Attention Detection0
A neuro-inspired system for online learning and recognition of parallel spike trains, based on spike latency and heterosynaptic STDP0
A New Method for Features Normalization in Motor Imagery Few-Shot Learning using Resting-State0
An intertwined neural network model for EEG classification in brain-computer interfaces0
A Novel Semi-supervised Meta Learning Method for Subject-transfer Brain-computer Interface0
Application of Common Spatial Patterns in Gravitational Waves Detection0
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works0
Are Brain-Computer Interfaces Feasible with Integrated Photonic Chips?0
ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for Arabic Characters0
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