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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

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Showing 291–300 of 466 papers

TitleStatusHype
Are Brain-Computer Interfaces Feasible with Integrated Photonic Chips?—0
End-to-end translation of human neural activity to speech with a dual-dual generative adversarial network—0
Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings—0
A case study on profiling of an EEG-based brain decoding interface on Cloud and Edge servers—0
EEGDnet: Fusing Non-Local and Local Self-Similarity for 1-D EEG Signal Denoising with 2-D Transformer—0
Online Optimization of Stimulation Speed in an Auditory Brain-Computer Interface under Time Constraints—0
EEG-based Classification of Drivers Attention using Convolutional Neural Network—0
Generating Music and Generative Art from Brain activity—0
A SPA-based Manifold Learning Framework for Motor Imagery EEG Data Classification—0
Voxel selection framework based on meta-heuristic search and mutual information for brain decoding—0
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