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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 121130 of 466 papers

TitleStatusHype
Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets0
Spatiotemporal Pooling on Appropriate Topological Maps Represented as Two-Dimensional Images for EEG Classification0
FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network0
NeuSpeech: Decode Neural signal as SpeechCode3
Stimulation technology for brain and nerves, now and future0
Towards Decoding Brain Activity During Passive Listening of SpeechCode0
ArEEG_Chars: Dataset for Envisioned Speech Recognition using EEG for Arabic Characters0
Early feasibility of an embedded bi-directional brain-computer interface for ambulation0
Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial NetworksCode1
Classification of Emerging Neural Activity from Planning to Grasp Execution using a Novel EEG-Based BCI Platform0
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