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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 211220 of 466 papers

TitleStatusHype
Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition0
Classification of Emerging Neural Activity from Planning to Grasp Execution using a Novel EEG-Based BCI Platform0
Classification of fNIRS Data Under Uncertainty: A Bayesian Neural Network Approach0
Automatic Muscle Artifacts Identification and Removal from Single-Channel EEG Using Wavelet Transform with Meta-heuristically Optimized Non-local Means Filter0
DeepBrain: Towards Personalized EEG Interaction through Attentional and Embedded LSTM Learning0
FingerNet: EEG Decoding of A Fine Motor Imagery with Finger-tapping Task Based on A Deep Neural Network0
From Theory to Application: Fine-Tuning Large EEG Model with Real-World Stress Data0
Automatic Control of Reactive Brain Computer Interfaces0
Fuzzy temporal convolutional neural networks in P300-based Brain-computer interface for smart home interaction0
A multi-agent control framework for co-adaptation in brain-computer interfaces0
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