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

• URL: http://arxiv.org/abs/2307.02819v1
• Date: Thu, 6 Jul 2023 07:24:38 GMT
• Title: Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers
• Authors: Nathan Koome Murungi, Michael Vinh Pham, Xufeng Dai, Xiaodong Qu
• Abstract summary: 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.
• Score: 0.08921166277011344
• License: http://creativecommons.org/licenses/by/4.0/
• 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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