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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 110 of 466 papers

TitleStatusHype
NeuSpeech: Decode Neural signal as SpeechCode3
CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery ClassificationCode3
PHemoNet: A Multimodal Network for Physiological SignalsCode2
Guess What I Think: Streamlined EEG-to-Image Generation with Latent Diffusion ModelsCode2
Multi-scale convolutional transformer network for motor imagery brain-computer interfaceCode2
Neuro-GPT: Towards A Foundation Model for EEGCode2
Brain-Computer-Interface controlled robot via RaspberryPi and PiEEGCode2
https://arxiv.org/pdf/2409.07491Code2
GCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery SignalsCode2
Physics-inform attention temporal convolutional network for EEG-based motor imagery classificationCode2
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