Trends in Machine Learning and Electroencephalogram (EEG): A Review for
  Undergraduate Researchers
Nathan Koome Murungi Michael Vinh Pham Xufeng Dai Xiaodong Qu
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.