medical-2
Brain Computer Interface
3260 papers • 126 benchmarks • 313 datasets
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.
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Transformer-based Spatial-Temporal Feature Learning for EEG Decoding
Yonghao Song, Xueyu Jia, Lie Yang, Longhan Xie•Thu Jun 10 2021
A novel EEG decoding method that mainly relies on the attention mechanism, which has good potential to promote the practicality of brain-computer interface (BCI) and is the first time that a detailed and complete method based on the transformer idea has been proposed.
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