This chapter provides a foundational understanding of electroencephalography (EEG) signals, focusing on their generation, acquisition, and the datasets relevant to brain fingerprint identification. The chapter begins with a detailed discussion of how EEG signals are generated through the electrical activity of neurons in the brain. It explains the mechanisms underlying neuronal communication and the resultant electrical potentials that can be captured at the scalp using electrodes. This section establishes the biological basis for EEG signal acquisition and highlights the significance of signal characteristics in the context of identity recognition. Following the generation of EEG signals, the chapter addresses the acquisition process, outlining the technical aspects of EEG recording, including electrode placement, signal amplification, and noise reduction techniques. It emphasizes the importance of proper acquisition methods to ensure high-quality data for subsequent analysis. The chapter concludes with an overview of EEG datasets specifically curated for brain fingerprint identification. This section discusses the criteria for dataset selection, the diversity of stimuli used in experiments, and the relevance of these datasets for training and validating brain fingerprint identification algorithms. By providing a comprehensive understanding of EEG signals and their application in brain fingerprint identification, this chapter lays the groundwork for the advanced methodologies and analyses explored in the subsequent chapters of the book.