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.
@article{arxiv.2307.02819,
title = {Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers},
author = {Nathan Koome Murungi and Michael Vinh Pham and Xufeng Dai and Xiaodong Qu},
journal= {arXiv preprint arXiv:2307.02819},
year = {2023}
}
Comments
14 pages, 1 figure, HCI International 2023 Conference