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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 331340 of 466 papers

TitleStatusHype
Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG0
Minimizing inter-subject variability in fNIRS based Brain Computer Interfaces via multiple-kernel support vector learning0
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions0
Motor Imagery Classification of Single-Arm Tasks Using Convolutional Neural Network based on Feature Refining0
Motor imagery classification using EEG spectrograms0
Motor Imagery EEG Signals: Multi-Task Classification and Subject Identification with a Lightweight CNN0
Multiagent Copilot Approach for Shared Autonomy between Human EEG and TD3 Deep Reinforcement Learning0
Multiclass Common Spatial Pattern for EEG based Brain Computer Interface with Adaptive Learning Classifier0
Multimodal Brain-Computer Interface for In-Vehicle Driver Cognitive Load Measurement: Dataset and Baselines0
Multimodal Classification with Deep Convolutional-Recurrent Neural Networks for Electroencephalography0
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