Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers

July 06, 2023 Β· The Cartographer Β· πŸ› InteracciΓ³n

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"Title-pattern auto-detect: Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers"

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Authors Nathan Koome Murungi, Michael Vinh Pham, Xufeng Dai, Xiaodong Qu arXiv ID 2307.02819 Category cs.HC: Human-Computer Interaction Cross-listed cs.LG Citations 17 Venue InteracciΓ³n Last Checked 2 days ago
Abstract
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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