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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 321330 of 466 papers

TitleStatusHype
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions0
4D Attention-based Neural Network for EEG Emotion Recognition0
Real or Virtual? Using Brain Activity Patterns to differentiate Attended Targets during Augmented Reality Scenarios0
In-Ear SpO2 for Classification of Cognitive Workload0
Towards Real-World BCI: CCSPNet, A Compact Subject-Independent Motor Imagery FrameworkCode0
Comparison of Classification Algorithms Towards Subject-Specific and Subject-Independent BCICode0
Improving EEG Decoding via Clustering-based Multi-task Feature Learning0
Light-Weight 1-D Convolutional Neural Network Architecture for Mental Task Identification and Classification Based on Single-Channel EEG0
An algorithm for onset detection of linguistic segments in continuous electroencephalogram signalsCode0
T-WaveNet: Tree-Structured Wavelet Neural Network for Sensor-Based Time Series Analysis0
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