Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers
July 06, 2023 Β· The Cartographer Β· π 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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