HCLGJul 6, 2023

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

arXiv:2307.02819v119 citationsh-index: 13
Originality Synthesis-oriented
AI Analysis

It serves as an introductory guide for undergraduate researchers in the BCI field, but is incremental as it reviews existing work without new findings.

This paper provides a systematic literature review on Brain-Computer Interfaces (BCIs) using EEG, synthesizing recent trends to offer an accessible overview 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 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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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