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A review of researches on electroencephalogram decoding algorithms in brain-computer interface / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 856-861, 2019.
Article in Chinese | WPRIM | ID: wpr-774132
ABSTRACT
Brain-computer interface (BCI) provides a direct communicating and controlling approach between the brain and surrounding environment, which attracts a wide range of interest in the fields of brain science and artificial intelligence. It is a core to decode the electroencephalogram (EEG) feature in the BCI system. The decoding efficiency highly depends on the feature extraction and feature classification algorithms. In this paper, we first introduce the commonly-used EEG features in the BCI system. Then we introduce the basic classical algorithms and their advanced versions used in the BCI system. Finally, we present some new BCI algorithms proposed in recent years. We hope this paper can spark fresh thinking for the research and development of high-performance BCI system.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Physiology / Algorithms / Brain / Pattern Recognition, Automated / Electroencephalography / Brain-Computer Interfaces Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2019 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Physiology / Algorithms / Brain / Pattern Recognition, Automated / Electroencephalography / Brain-Computer Interfaces Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2019 Type: Article