Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers
This paper presents a systematic literature review on Brain-Computer Interfaces (BCIs) in the context of Machine Learning. Our focus is on Electroencephalography (EEG) research, highlighting the latest trends as of 2023. The objective is to provide undergraduate researchers with an accessible overvi...
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| creator | Murungi, Nathan Koome Pham, Michael Vinh Dai, Xufeng Qu, Xiaodong |
| description | This paper presents a systematic literature review on Brain-Computer Interfaces (BCIs) in the context of Machine Learning. Our focus is on Electroencephalography (EEG) research, highlighting the latest trends as of 2023. The objective is to provide undergraduate researchers with an accessible overview of the BCI field, covering tasks, algorithms, and datasets. By synthesizing recent findings, our aim is to offer a fundamental understanding of BCI research, identifying promising avenues for future investigations. |
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| subjects | Algorithms Electroencephalography Human-computer interface Literature reviews Machine learning Trends |
| title | Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers |
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