A Preliminary Study on Open-Source EEG Datasets: Human and GPT-Based Review and Cross-Dataset Classification

This study explores reproducible machine learning approaches for classifying EEG signals using open-source datasets. Leveraging publicly available data, the research focuses on developing and evaluating classification models that can be easily replicated and validated by other researchers. The results aim to contribute to the broader field of neural signal processing by demonstrating the potential of transparent and accessible methods for EEG analysis.